<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Greene, Daniel</style></author><author><style face="normal" font="default" size="100%">De Wispelaere, Koenraad</style></author><author><style face="normal" font="default" size="100%">Lees, Jon</style></author><author><style face="normal" font="default" size="100%">Codina-Solà, Marta</style></author><author><style face="normal" font="default" size="100%">Jensson, Brynjar O.</style></author><author><style face="normal" font="default" size="100%">Hales, Emma</style></author><author><style face="normal" font="default" size="100%">Katrinecz, Andrea</style></author><author><style face="normal" font="default" size="100%">Nieto Molina, Esther</style></author><author><style face="normal" font="default" size="100%">Sevilla Porras, Marta</style></author><author><style face="normal" font="default" size="100%">Pascoal, Sonia</style></author><author><style face="normal" font="default" size="100%">Valenzuela, Irene</style></author><author><style face="normal" font="default" size="100%">Pfundt, Rolph</style></author><author><style face="normal" font="default" size="100%">Schot, Rachel</style></author><author><style face="normal" font="default" size="100%">Sleutels, Frank</style></author><author><style face="normal" font="default" size="100%">Wijngaard, Robin</style></author><author><style face="normal" font="default" size="100%">Arroyo Carrera, Ignacio</style></author><author><style face="normal" font="default" size="100%">Duat Rodríguez, Anna</style></author><author><style face="normal" font="default" size="100%">Atton, Giles</style></author><author><style face="normal" font="default" size="100%">Casas-Alba, Didac</style></author><author><style face="normal" font="default" size="100%">Donnelly, Deirdre</style></author><author><style face="normal" font="default" size="100%">Fernández Garoz, Bárbara</style></author><author><style face="normal" font="default" size="100%">Foulds, Nicola</style></author><author><style face="normal" font="default" size="100%">García-Navas Núñez, Deyanira</style></author><author><style face="normal" font="default" size="100%">González Alguacil, Elena</style></author><author><style face="normal" font="default" size="100%">Jarvis, Joanna</style></author><author><style face="normal" font="default" size="100%">Kant, Sarina G.</style></author><author><style face="normal" font="default" size="100%">Madrigal Bajo, Irene</style></author><author><style face="normal" font="default" size="100%">Martinez-Monseny, Antonio F.</style></author><author><style face="normal" font="default" size="100%">McKee, Shane</style></author><author><style face="normal" font="default" size="100%">Sariego Jamardo, Andrea</style></author><author><style face="normal" font="default" size="100%">Stefansson, Kari</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Revenga Bodi, Laia</style></author><author><style face="normal" font="default" size="100%">Ortiz Cabrera, Nelmar Valentina</style></author><author><style face="normal" font="default" size="100%">Sulem, Patrick</style></author><author><style face="normal" font="default" size="100%">Suri, Mohnish</style></author><author><style face="normal" font="default" size="100%">Van Karnebeek, Clara</style></author><author><style face="normal" font="default" size="100%">Vasudevan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Vega Pajares, Ana Isabel</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Engelen, Marc</style></author><author><style face="normal" font="default" size="100%">Lapunzina, Pablo</style></author><author><style face="normal" font="default" size="100%">Morgan, Natasha P.</style></author><author><style face="normal" font="default" size="100%">Morte, Beatriz</style></author><author><style face="normal" font="default" size="100%">Rump, Patrick</style></author><author><style face="normal" font="default" size="100%">Stirrups, Kathy</style></author><author><style face="normal" font="default" size="100%">Tizzano, Eduardo F.</style></author><author><style face="normal" font="default" size="100%">Barakat, Tahsin Stefan</style></author><author><style face="normal" font="default" size="100%">O’Donoghue, Michael</style></author><author><style face="normal" font="default" size="100%">Pérez-Jurado, Luis Alberto</style></author><author><style face="normal" font="default" size="100%">Freson, Kathleen</style></author><author><style face="normal" font="default" size="100%">Mumford, Andrew D.</style></author><author><style face="normal" font="default" size="100%">Turro, Ernest</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutations in the small nuclear RNA gene RNU2-2 cause a severe neurodevelopmental disorder with prominent epilepsy</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Genetics</style></secondary-title><short-title><style face="normal" font="default" size="100%">Nat Genet</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct-04-2025</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/s41588-025-02159-5https://www.nature.com/articles/s41588-025-02159-5.pdfhttps://www.nature.com/articles/s41588-025-02159-5.pdfhttps://www.nature.com/articles/s41588-025-02159-5</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Loucera-Muñecas, C</style></author><author><style face="normal" font="default" size="100%">Canal-Rivero, M</style></author><author><style face="normal" font="default" size="100%">Ruiz-Veguilla, M</style></author><author><style face="normal" font="default" size="100%">Carmona, R</style></author><author><style face="normal" font="default" size="100%">Bostelmann, G</style></author><author><style face="normal" font="default" size="100%">Garrido-Torres, N</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Crespo-Facorro, B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Aripiprazole as protector against COVID-19 mortality.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">Antipsychotic Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Aripiprazole</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19 Drug Treatment</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 May 29</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">12362</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The relation of antipsychotics with severe Coronavirus Disease 19 (COVID-19) outcomes is a matter of debate since the beginning of the pandemic. To date, controversial results have been published on this issue. We aimed to prove whether antipsychotics might exert adverse or protective effects against fatal outcomes derived from COVID-19. A population-based retrospective cohort study (January 2020 to November 2020) comprising inpatients (15,968 patients) who were at least 18 years old and had a laboratory-confirmed COVID-19 infection. Two sub-cohorts were delineated, comprising a total of 2536 inpatients: individuals who either had no prescription medication or were prescribed an antipsychotic within the 15 days preceding hospitalization. We conducted survival and odds ratio analyses to assess the association between antipsychotic use and mortality, reporting both unadjusted and covariate-adjusted results. We computed the average treatment effects, using the untreated group as the reference, and the average treatment effect on the treated, focusing solely on the antipsychotic-treated population. Among the eight antipsychotics found to be in use, only aripiprazole showed a significant decrease in the risk of death from COVID-19 [adjusted odds ratio (OR) = 0.86; 95% CI, 0.79-0.93, multiple-testing adjusted p-value &lt; 0.05]. Importantly, these findings were consistent for both covariate-adjusted and unadjusted analyses. Aripiprazole has been shown to have a differentiated beneficial effect in protecting against fatal clinical outcome in COVID-19 infected individuals. We speculate that the differential effect of aripiprazole on controlling immunological pathways and inducible inflammatory enzymes, that are critical in COVID19 illness, may be associated with our findings herein.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">de la Oliva Roque, Víctor Manuel</style></author><author><style face="normal" font="default" size="100%">Herráiz-Gil, Sara</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">drexml: A command line tool and Python package for drug repurposing.</style></title><secondary-title><style face="normal" font="default" size="100%">Comput Struct Biotechnol J</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Comput Struct Biotechnol J</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Dec</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">1129-1143</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Niarakis, Anna</style></author><author><style face="normal" font="default" size="100%">Ostaszewski, Marek</style></author><author><style face="normal" font="default" size="100%">Mazein, Alexander</style></author><author><style face="normal" font="default" size="100%">Kuperstein, Inna</style></author><author><style face="normal" font="default" size="100%">Kutmon, Martina</style></author><author><style face="normal" font="default" size="100%">Gillespie, Marc E</style></author><author><style face="normal" font="default" size="100%">Funahashi, Akira</style></author><author><style face="normal" font="default" size="100%">Acencio, Marcio Luis</style></author><author><style face="normal" font="default" size="100%">Hemedan, Ahmed</style></author><author><style face="normal" font="default" size="100%">Aichem, Michael</style></author><author><style face="normal" font="default" size="100%">Klein, Karsten</style></author><author><style face="normal" font="default" size="100%">Czauderna, Tobias</style></author><author><style face="normal" font="default" size="100%">Burtscher, Felicia</style></author><author><style face="normal" font="default" size="100%">Yamada, Takahiro G</style></author><author><style face="normal" font="default" size="100%">Hiki, Yusuke</style></author><author><style face="normal" font="default" size="100%">Hiroi, Noriko F</style></author><author><style face="normal" font="default" size="100%">Hu, Finterly</style></author><author><style face="normal" font="default" size="100%">Pham, Nhung</style></author><author><style face="normal" font="default" size="100%">Ehrhart, Friederike</style></author><author><style face="normal" font="default" size="100%">Willighagen, Egon L</style></author><author><style face="normal" font="default" size="100%">Valdeolivas, Alberto</style></author><author><style face="normal" font="default" size="100%">Dugourd, Aurélien</style></author><author><style face="normal" font="default" size="100%">Messina, Francesco</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Soliman, Sylvain</style></author><author><style face="normal" font="default" size="100%">Aghamiri, Sara Sadat</style></author><author><style face="normal" font="default" size="100%">Puniya, Bhanwar Lal</style></author><author><style face="normal" font="default" size="100%">Naldi, Aurélien</style></author><author><style face="normal" font="default" size="100%">Helikar, Tomáš</style></author><author><style face="normal" font="default" size="100%">Singh, Vidisha</style></author><author><style face="normal" font="default" size="100%">Fernández, Marco Fariñas</style></author><author><style face="normal" font="default" size="100%">Bermudez, Viviam</style></author><author><style face="normal" font="default" size="100%">Tsirvouli, Eirini</style></author><author><style face="normal" font="default" size="100%">Montagud, Arnau</style></author><author><style face="normal" font="default" size="100%">Noël, Vincent</style></author><author><style face="normal" font="default" size="100%">Ponce-de-Leon, Miguel</style></author><author><style face="normal" font="default" size="100%">Maier, Dieter</style></author><author><style face="normal" font="default" size="100%">Bauch, Angela</style></author><author><style face="normal" font="default" size="100%">Gyori, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Bachman, John A</style></author><author><style face="normal" font="default" size="100%">Luna, Augustin</style></author><author><style face="normal" font="default" size="100%">Piñero, Janet</style></author><author><style face="normal" font="default" size="100%">Furlong, Laura I</style></author><author><style face="normal" font="default" size="100%">Balaur, Irina</style></author><author><style face="normal" font="default" size="100%">Rougny, Adrien</style></author><author><style face="normal" font="default" size="100%">Jarosz, Yohan</style></author><author><style face="normal" font="default" size="100%">Overall, Rupert W</style></author><author><style face="normal" font="default" size="100%">Phair, Robert</style></author><author><style face="normal" font="default" size="100%">Perfetto, Livia</style></author><author><style face="normal" font="default" size="100%">Matthews, Lisa</style></author><author><style face="normal" font="default" size="100%">Rex, Devasahayam Arokia Balaya</style></author><author><style face="normal" font="default" size="100%">Orlic-Milacic, Marija</style></author><author><style face="normal" font="default" size="100%">Gomez, Luis Cristobal Monraz</style></author><author><style face="normal" font="default" size="100%">De Meulder, Bertrand</style></author><author><style face="normal" font="default" size="100%">Ravel, Jean Marie</style></author><author><style face="normal" font="default" size="100%">Jassal, Bijay</style></author><author><style face="normal" font="default" size="100%">Satagopam, Venkata</style></author><author><style face="normal" font="default" size="100%">Wu, Guanming</style></author><author><style face="normal" font="default" size="100%">Golebiewski, Martin</style></author><author><style face="normal" font="default" size="100%">Gawron, Piotr</style></author><author><style face="normal" font="default" size="100%">Calzone, Laurence</style></author><author><style face="normal" font="default" size="100%">Beckmann, Jacques S</style></author><author><style face="normal" font="default" size="100%">Evelo, Chris T</style></author><author><style face="normal" font="default" size="100%">D'Eustachio, Peter</style></author><author><style face="normal" font="default" size="100%">Schreiber, Falk</style></author><author><style face="normal" font="default" size="100%">Saez-Rodriguez, Julio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Kuiper, Martin</style></author><author><style face="normal" font="default" size="100%">Valencia, Alfonso</style></author><author><style face="normal" font="default" size="100%">Wolkenhauer, Olaf</style></author><author><style face="normal" font="default" size="100%">Kitano, Hiroaki</style></author><author><style face="normal" font="default" size="100%">Barillot, Emmanuel</style></author><author><style face="normal" font="default" size="100%">Auffray, Charles</style></author><author><style face="normal" font="default" size="100%">Balling, Rudi</style></author><author><style face="normal" font="default" size="100%">Schneider, Reinhard</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">COVID-19 Disease Map Community</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.</style></title><secondary-title><style face="normal" font="default" size="100%">Front Immunol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Front Immunol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">drug repositioning</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems biology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">1282859</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;INTRODUCTION: &lt;/b&gt;The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.&lt;/p&gt;&lt;p&gt;&lt;b&gt;DISCUSSION: &lt;/b&gt;The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fernández-Palacios, Pablo</style></author><author><style face="normal" font="default" size="100%">Galán-Sánchez, Fátima</style></author><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Jurado-Tarifa, Estefanía</style></author><author><style face="normal" font="default" size="100%">Arroyo, Federico</style></author><author><style face="normal" font="default" size="100%">Lara, María</style></author><author><style face="normal" font="default" size="100%">Chaves, J Alberto</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Iglesias, Manuel A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genotypic characterization and antimicrobial susceptibility of human  isolates in Southern Spain.</style></title><secondary-title><style face="normal" font="default" size="100%">Microbiol Spectr</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Microbiol Spectr</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">Anti-Bacterial Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Campylobacter Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">Campylobacter jejuni</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Ciprofloxacin</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug Resistance, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Erythromycin</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbial Sensitivity Tests</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Tetracycline</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Oct 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">e0102824</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt; is the main cause of bacterial gastroenteritis and a public health problem worldwide. Little information is available on the genotypic characteristics of human  in Spain. This study is based on an analysis of the resistome, virulome, and phylogenetic relationship, antibiogram prediction, and antimicrobial susceptibility of 114 human isolates of  from a tertiary hospital in southern Spain from October 2020 to June 2023. The isolates were sequenced using Illumina technology, and a bioinformatic analysis was subsequently performed. The susceptibility of  isolates to ciprofloxacin, tetracycline, and erythromycin was also tested. The resistance rates for each antibiotic were 90.3% for ciprofloxacin, 66.7% for tetracycline, and 0.88% for erythromycin. The fluoroquinolone resistance rate obtained is well above the European average (69.1%). CC-21 ( = 23), ST-572 ( = 13), and ST-6532 ( = 13) were the most prevalent clonal complexes (CCs) and sequence types (STs). In the virulome, the , and  genes were detected in all the isolates. A prevalence of 20.1% was obtained for the genes  and , which are related to the pathogenesis of Guillain-Barré syndrome (GBS). The prevalence of the main antimicrobial resistance markers detected were CmeABC (92.1%), RE-cmeABC (7.9%), the T86I substitution in  (88.9%),  (72.6%) (65.8%), and  (17.1%). High antibiogram prediction rates (&gt;97%) were obtained, except for in the case of the erythromycin-resistant phenotype. This study contributes significantly to the knowledge of  genomics for the prevention, treatment, and control of infections caused by this pathogen.IMPORTANCEDespite being the pathogen with the greatest number of gastroenteritis cases worldwide,  remains a poorly studied microorganism. A sustained increase in fluoroquinolone resistance in human isolates is a problem when treating  infections. The development of whole genome sequencing (WGS) techniques has allowed us to better understand the genotypic characteristics of this pathogen and relate them to antibiotic resistance phenotypes. These techniques complement the data obtained from the phenotypic analysis of  isolates. The zoonotic transmission of  through the consumption of contaminated poultry supports approaching the study of this pathogen through &quot;One Health&quot; approach. In addition, due to the limited information on the genomic characteristics of  in Spain, this study provides important data and allows us to compare the results with those obtained in other countries.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">Mondaza-Hernandez, Jose L</style></author><author><style face="normal" font="default" size="100%">Sanchez-Bustos, Paloma</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Cordero-Varela, Juan A</style></author><author><style face="normal" font="default" size="100%">Lopez-Alvarez, Maria</style></author><author><style face="normal" font="default" size="100%">Carrillo-Garcia, Jaime</style></author><author><style face="normal" font="default" size="100%">Martin-Ruiz, Marta</style></author><author><style face="normal" font="default" size="100%">Romero-Gonzalez, Pablo</style></author><author><style face="normal" font="default" size="100%">Renshaw-Calderon, Marta</style></author><author><style face="normal" font="default" size="100%">Ramos, Rafael</style></author><author><style face="normal" font="default" size="100%">Marcilla, David</style></author><author><style face="normal" font="default" size="100%">Alvarez-Alegret, Ramiro</style></author><author><style face="normal" font="default" size="100%">Agra-Pujol, Carolina</style></author><author><style face="normal" font="default" size="100%">Izquierdo, Francisco</style></author><author><style face="normal" font="default" size="100%">Ortega-Medina, Luis</style></author><author><style face="normal" font="default" size="100%">Martin-Davila, Francisco</style></author><author><style face="normal" font="default" size="100%">Hernandez-Leon, Carmen Nieves</style></author><author><style face="normal" font="default" size="100%">Romagosa, Cleofe</style></author><author><style face="normal" font="default" size="100%">Salgado, Maria Angeles Vaz</style></author><author><style face="normal" font="default" size="100%">Lavernia, Javier</style></author><author><style face="normal" font="default" size="100%">Bagué, Silvia</style></author><author><style face="normal" font="default" size="100%">Mayodormo-Aranda, Empar</style></author><author><style face="normal" font="default" size="100%">Alvarez, Rosa</style></author><author><style face="normal" font="default" size="100%">Valverde, Claudia</style></author><author><style face="normal" font="default" size="100%">Martinez-Trufero, Javier</style></author><author><style face="normal" font="default" size="100%">Castilla-Ramirez, Carolina</style></author><author><style face="normal" font="default" size="100%">Gutierrez, Antonio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Garcia-Foncillas, Jesus</style></author><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Mol Life Sci</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell Mol Life Sci</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Antineoplastic Agents, Alkylating</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Line, Tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug Resistance, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">HMGA1a Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Leiomyosarcoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Sarcoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">TOR Serine-Threonine Kinases</style></keyword><keyword><style  face="normal" font="default" size="100%">Trabectedin</style></keyword><keyword><style  face="normal" font="default" size="100%">Xenograft Model Antitumor Assays</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 May 17</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">81</style></volume><pages><style face="normal" font="default" size="100%">219</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;HMGA1 is a structural epigenetic chromatin factor that has been associated with tumor progression and drug resistance. Here, we reported the prognostic/predictive value of HMGA1 for trabectedin in advanced soft-tissue sarcoma (STS) and the effect of inhibiting HMGA1 or the mTOR downstream pathway in trabectedin activity. The prognostic/predictive value of HMGA1 expression was assessed in a cohort of 301 STS patients at mRNA (n = 133) and protein level (n = 272), by HTG EdgeSeq transcriptomics and immunohistochemistry, respectively. The effect of HMGA1 silencing on trabectedin activity and gene expression profiling was measured in leiomyosarcoma cells. The effect of combining mTOR inhibitors with trabectedin was assessed on cell viability in vitro studies, whereas in vivo studies tested the activity of this combination. HMGA1 mRNA and protein expression were significantly associated with worse progression-free survival of trabectedin and worse overall survival in STS. HMGA1 silencing sensitized leiomyosarcoma cells for trabectedin treatment, reducing the spheroid area and increasing cell death. The downregulation of HGMA1 significantly decreased the enrichment of some specific gene sets, including the PI3K/AKT/mTOR pathway. The inhibition of mTOR, sensitized leiomyosarcoma cultures for trabectedin treatment, increasing cell death. In in vivo studies, the combination of rapamycin with trabectedin downregulated HMGA1 expression and stabilized tumor growth of 3-methylcholantrene-induced sarcoma-like models. HMGA1 is an adverse prognostic factor for trabectedin treatment in advanced STS. HMGA1 silencing increases trabectedin efficacy, in part by modulating the mTOR signaling pathway. Trabectedin plus mTOR inhibitors are active in preclinical models of sarcoma, downregulating HMGA1 expression levels and stabilizing tumor growth.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mavillard, Fabiola</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco M</style></author><author><style face="normal" font="default" size="100%">Valladares, Amador</style></author><author><style face="normal" font="default" size="100%">Álvarez-Villegas, Miren L</style></author><author><style face="normal" font="default" size="100%">Roldán, Gema</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Soriano, Manuel</style></author><author><style face="normal" font="default" size="100%">Susarte, Santiago</style></author><author><style face="normal" font="default" size="100%">Fuentes, Pilar</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Nuñez-Negrillo, Ana María</style></author><author><style face="normal" font="default" size="100%">Carvajal, Alejandra</style></author><author><style face="normal" font="default" size="100%">Morgado, Yolanda</style></author><author><style face="normal" font="default" size="100%">Arteaga, Daniel</style></author><author><style face="normal" font="default" size="100%">Ufano, Rosa</style></author><author><style face="normal" font="default" size="100%">Mir, Pablo</style></author><author><style face="normal" font="default" size="100%">Gamella, Juan F</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Paradas, Carmen</style></author><author><style face="normal" font="default" size="100%">Cabrera-Serrano, Macarena</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Iberian Roma Population Variant Server (IRPVS).</style></title><secondary-title><style face="normal" font="default" size="100%">J Genet Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Genet Genomics</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Mar 26</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Robles, Enrique A</style></author><author><style face="normal" font="default" size="100%">Lara, María</style></author><author><style face="normal" font="default" size="100%">Aguado, Andrea</style></author><author><style face="normal" font="default" size="100%">Rodríguez Iglesias, Manuel A</style></author><author><style face="normal" font="default" size="100%">Lepe, Jose A</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author><author><style face="normal" font="default" size="100%">Pérez-Alegre, Mónica</style></author><author><style face="normal" font="default" size="100%">Andújar, Eloísa</style></author><author><style face="normal" font="default" size="100%">Jiménez, Victoria E</style></author><author><style face="normal" font="default" size="100%">Camino, Lola P</style></author><author><style face="normal" font="default" size="100%">Loruso, Nicola</style></author><author><style face="normal" font="default" size="100%">Ameyugo, Ulises</style></author><author><style face="normal" font="default" size="100%">Vazquez, Isabel María</style></author><author><style face="normal" font="default" size="100%">Lozano, Carlota M</style></author><author><style face="normal" font="default" size="100%">Chaves, J Alberto</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug Resistance, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">One Health</style></keyword><keyword><style  face="normal" font="default" size="100%">Virulence Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Aug 19</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">19200</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The One Health approach, recognizing the interconnectedness of human, animal, and environmental health, has gained significance amid emerging zoonotic diseases and antibiotic resistance concerns. This paper aims to demonstrate the utility of a collaborative tool, the SIEGA, for monitoring infectious diseases across domains, fostering a comprehensive understanding of disease dynamics and risk factors, highlighting the pivotal role of One Health surveillance systems. Raw whole-genome sequencing is processed through different species-specific open software that additionally reports the presence of genes associated to anti-microbial resistances and virulence. The SIEGA application is a Laboratory Information Management System, that allows customizing reports, detect transmission chains, and promptly alert on alarming genetic similarities. The SIEGA initiative has successfully accumulated a comprehensive collection of more than 1900 bacterial genomes, including Salmonella enterica, Listeria monocytogenes, Campylobacter jejuni, Escherichia coli, Yersinia enterocolitica and Legionella pneumophila, showcasing its potential in monitoring pathogen transmission, resistance patterns, and virulence factors. SIEGA enables customizable reports and prompt detection of transmission chains, highlighting its contribution to enhancing vigilance and response capabilities. Here we show the potential of genomics in One Health surveillance when supported by an appropriate bioinformatic tool. By facilitating precise disease control strategies and antimicrobial resistance management, SIEGA enhances global health security and reduces the burden of infectious diseases. The integration of health data from humans, animals, and the environment, coupled with advanced genomics, underscores the importance of a holistic One Health approach in mitigating health threats.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Velasco, Sheyla</style></author><author><style face="normal" font="default" size="100%">Olivares-González, Lorena</style></author><author><style face="normal" font="default" size="100%">Rodrigo, Regina</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery.</style></title><secondary-title><style face="normal" font="default" size="100%">J Transl Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Transl Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Feb 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">139</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pérez-Gutiérrez, Ana M</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Cervilla, Jorge A</style></author><author><style face="normal" font="default" size="100%">Gutiérrez, Blanca</style></author><author><style face="normal" font="default" size="100%">Molina, Esther</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Zarza-Rebollo, Juan Antonio</style></author><author><style face="normal" font="default" size="100%">López-Isac, Elena</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martinez-Gonzalez, Luis Javier</style></author><author><style face="normal" font="default" size="100%">Rivera, Margarita</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Psychiatry</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Psychiatry</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 May 28</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Baz-Redón, Noelia</style></author><author><style face="normal" font="default" size="100%">Sánchez-Bellver, Laura</style></author><author><style face="normal" font="default" size="100%">Fernández-Cancio, Mónica</style></author><author><style face="normal" font="default" size="100%">Rovira-Amigo, Sandra</style></author><author><style face="normal" font="default" size="100%">Burgoyne, Thomas</style></author><author><style face="normal" font="default" size="100%">Ranjit, Rai</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">Toro-Barrios, Noemí</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Polverino, Eva</style></author><author><style face="normal" font="default" size="100%">Cols, Maria</style></author><author><style face="normal" font="default" size="100%">Moreno-Galdó, Antonio</style></author><author><style face="normal" font="default" size="100%">Camats-Tarruella, Núria</style></author><author><style face="normal" font="default" size="100%">Marfany, Gemma</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Primary Ciliary Dyskinesia and Retinitis Pigmentosa: Novel  Variant and Possible Modifier Gene.</style></title><secondary-title><style face="normal" font="default" size="100%">Cells</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cells</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ciliary Motility Disorders</style></keyword><keyword><style  face="normal" font="default" size="100%">Eye Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Modifier</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Mar 16</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We report a novel  missense variant co-segregated with a familial X-linked retinitis pigmentosa (XLRP) case. The brothers were hemizygous for this variant, but only the proband presented with primary ciliary dyskinesia (PCD). Thus, we aimed to elucidate the role of the  variant and other modifier genes in the phenotypic variability observed in the family and its impact on motile cilia. The pathogenicity of the variant on the RPGR protein was evaluated by in vitro studies transiently transfecting the mutated  gene, and immunofluorescence analysis on nasal brushing samples. Whole-exome sequencing was conducted to identify potential modifier variants. In vitro studies showed that the mutated RPGR protein could not localise to the cilium and impaired cilium formation. Accordingly, RPGR was abnormally distributed in the siblings' nasal brushing samples. In addition, a missense variant in  was identified. The concurrent  variant influenced ciliary mislocalisation of the protein. We provide a comprehensive characterisation of motile cilia in this XLRP family, with only the proband presenting PCD symptoms. The variant's pathogenicity was confirmed, although it alone does not explain the respiratory symptoms. Finally, the  gene may be a potential modifier for respiratory symptoms in patients with  mutations.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">López López, Daniel</style></author><author><style face="normal" font="default" size="100%">di Lernia, Davide</style></author><author><style face="normal" font="default" size="100%">Martin-Ruiz, Marta</style></author><author><style face="normal" font="default" size="100%">Lopez-Alvarez, Maria</style></author><author><style face="normal" font="default" size="100%">Ramos, Rafael</style></author><author><style face="normal" font="default" size="100%">Merino, Jose</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Lopez-Guerrero, Jose</style></author><author><style face="normal" font="default" size="100%">Mondaza-Hernandez, Jose L</style></author><author><style face="normal" font="default" size="100%">Romero, Pablo</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Garcia-Foncillas, Jesus</style></author><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Shared germline genomic variants in two patients with double primary gastrointestinal stromal tumours (GISTs).</style></title><secondary-title><style face="normal" font="default" size="100%">J Med Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Med Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gastrointestinal Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Gastrointestinal Stromal Tumors</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Germ-Line Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Proto-Oncogene Proteins c-kit</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptor, Platelet-Derived Growth Factor alpha</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Sep 24</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">927-934</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Gastrointestinal stromal tumours (GISTs) are prevalent mesenchymal tumours of the gastrointestinal tract, commonly exhibiting structural variations in  and  genes. While the mutational profiling of somatic tumours is well described, the genes behind the susceptibility to develop GIST are not yet fully discovered. This study explores the genomic landscape of two primary GIST cases, aiming to identify shared germline pathogenic variants and shed light on potential key players in tumourigenesis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Two patients with distinct genotypically and phenotypically GISTs underwent germline whole genome sequencing. CNV and single nucleotide variant (SNV) analyses were performed.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Both patients harbouring low-risk GISTs with different mutations ( and ) shared homozygous germline pathogenic deletions in both  and  genes. CNV analysis revealed additional shared pathogenic deletions in other genes such as . No particular pathogenic SNV shared by both patients was detected.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;Our study provides new insights into germline variants that can be associated with the development of GISTs, namely,  and  deep deletions. Further functional validation is warranted to elucidate the precise contributions of identified germline mutations in GIST development.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Blasco, Lucia</style></author><author><style face="normal" font="default" size="100%">López-Hernández, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Fernández, Miguel</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Case report: Analysis of phage therapy failure in a patient with a Pseudomonas aeruginosa prosthetic vascular graft infection</style></title><secondary-title><style face="normal" font="default" size="100%">Front Med (Lausanne)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Front Med (Lausanne)</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235614/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">1199657</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Clinical case of a patient with a  multidrug-resistant prosthetic vascular graft infection which was treated with a cocktail of phages (PT07, 14/01, and PNM) in combination with ceftazidime-avibactam (CZA). After the application of the phage treatment and in absence of antimicrobial therapy, a new  bloodstream infection (BSI) with a septic residual limb metastasis occurred, now involving a wild-type strain being susceptible to ß-lactams and quinolones. Clinical strains were analyzed by microbiology and whole genome sequencing techniques. In relation with phage administration, the clinical isolates of  before phage therapy (HE2011471) and post phage therapy (HE2105886) showed a clonal relationship but with important genomic changes which could be involved in the resistance to this therapy. Finally, phenotypic studies showed a decrease in Minimum Inhibitory Concentration (MIC) to ß-lactams and quinolones as well as an increase of the biofilm production and phage resistant mutants in the clinical isolate of  post phage therapy.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Núñez-Torres, Rocío</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Zamora, Jorge</style></author><author><style face="normal" font="default" size="100%">Roldán, Gema</style></author><author><style face="normal" font="default" size="100%">Herráez, Belén</style></author><author><style face="normal" font="default" size="100%">Alvarez, Nuria</style></author><author><style face="normal" font="default" size="100%">Alonso, María Rosario</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">González-Neira, Anna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact.</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmaceutics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Pharmaceutics</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Apr 19</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">15</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Roldán, Gema</style></author><author><style face="normal" font="default" size="100%">Fernandez-Rueda, Jose L</style></author><author><style face="normal" font="default" size="100%">Bostelmann, Gerrit</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Núñez-Torres, Rocío</style></author><author><style face="normal" font="default" size="100%">González-Neira, Anna</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">CSVS Crowdsourcing Group</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">A crowdsourcing database for the copy-number variation of the Spanish population.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Genomics</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Mar 09</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">20</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ .&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pellegrinelli, Vanessa</style></author><author><style face="normal" font="default" size="100%">Figueroa-Juárez, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Samuelson, Isabella</style></author><author><style face="normal" font="default" size="100%">U-Din, Mueez</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Fdez, Sonia</style></author><author><style face="normal" font="default" size="100%">Virtue, Samuel</style></author><author><style face="normal" font="default" size="100%">Leggat, Jennifer</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Peirce, Vivian J</style></author><author><style face="normal" font="default" size="100%">Niemi, Tarja</style></author><author><style face="normal" font="default" size="100%">Campbell, Mark</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Cuenca, Sergio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Carobbio, Stefania</style></author><author><style face="normal" font="default" size="100%">Virtanen, Kirsi A</style></author><author><style face="normal" font="default" size="100%">Vidal-Puig, Antonio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Defective extracellular matrix remodeling in brown adipose tissue is associated with fibro-inflammation and reduced diet-induced thermogenesis.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell Rep</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Jun 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">112640</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The relevance of extracellular matrix (ECM) remodeling is reported in white adipose tissue (AT) and obesity-related dysfunctions, but little is known about the importance of ECM remodeling in brown AT (BAT) function. Here, we show that a time course of high-fat diet (HFD) feeding progressively impairs diet-induced thermogenesis concomitantly with the development of fibro-inflammation in BAT. Higher markers of fibro-inflammation are associated with lower cold-induced BAT activity in humans. Similarly, when mice are housed at thermoneutrality, inactivated BAT features fibro-inflammation. We validate the pathophysiological relevance of BAT ECM remodeling in response to temperature challenges and HFD using a model of a primary defect in the collagen turnover mediated by partial ablation of the Pepd prolidase. Pepd-heterozygous mice display exacerbated dysfunction and BAT fibro-inflammation at thermoneutrality and in HFD. Our findings show the relevance of ECM remodeling in BAT activation and provide a mechanism for BAT dysfunction in obesity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco</style></author><author><style face="normal" font="default" size="100%">Fernandez-Rueda, Jose L</style></author><author><style face="normal" font="default" size="100%">Aguado, Andrea</style></author><author><style face="normal" font="default" size="100%">Lara, María</style></author><author><style face="normal" font="default" size="100%">Riazzo, Cristina</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Iglesias, Manuel A</style></author><author><style face="normal" font="default" size="100%">Camacho-Martinez, Pedro</style></author><author><style face="normal" font="default" size="100%">Merino-Diaz, Laura</style></author><author><style face="normal" font="default" size="100%">Pupo-Ledo, Inmaculada</style></author><author><style face="normal" font="default" size="100%">de Salazar, Adolfo</style></author><author><style face="normal" font="default" size="100%">Viñuela, Laura</style></author><author><style face="normal" font="default" size="100%">Fuentes, Ana</style></author><author><style face="normal" font="default" size="100%">Chueca, Natalia</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Lepe, Jose A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia.</style></title><secondary-title><style face="normal" font="default" size="100%">Int J Mol Sci</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Int J Mol Sci</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Jan 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">24</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sola-García, Alejandro</style></author><author><style face="normal" font="default" size="100%">Cáliz-Molina, María Ángeles</style></author><author><style face="normal" font="default" size="100%">Espadas, Isabel</style></author><author><style face="normal" font="default" size="100%">Petr, Michael</style></author><author><style face="normal" font="default" size="100%">Panadero-Morón, Concepción</style></author><author><style face="normal" font="default" size="100%">González-Morán, Daniel</style></author><author><style face="normal" font="default" size="100%">Martín-Vázquez, María Eugenia</style></author><author><style face="normal" font="default" size="100%">Narbona-Pérez, Álvaro Jesús</style></author><author><style face="normal" font="default" size="100%">López-Noriega, Livia</style></author><author><style face="normal" font="default" size="100%">Martínez-Corrales, Guillermo</style></author><author><style face="normal" font="default" size="100%">López-Fernández-Sobrino, Raúl</style></author><author><style face="normal" font="default" size="100%">Carmona-Marin, Lina M</style></author><author><style face="normal" font="default" size="100%">Martínez-Force, Enrique</style></author><author><style face="normal" font="default" size="100%">Yanes, Oscar</style></author><author><style face="normal" font="default" size="100%">Vinaixa, Maria</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Reyes, José Carlos</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Martín, Franz</style></author><author><style face="normal" font="default" size="100%">Gauthier, Benoit R</style></author><author><style face="normal" font="default" size="100%">Scheibye-Knudsen, Morten</style></author><author><style face="normal" font="default" size="100%">Capilla-González, Vivian</style></author><author><style face="normal" font="default" size="100%">Martín-Montalvo, Alejandro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging.</style></title><secondary-title><style face="normal" font="default" size="100%">Commun Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Commun Biol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Mar 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">250</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;ATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Corrales, Patricia</style></author><author><style face="normal" font="default" size="100%">Martin-Taboada, Marina</style></author><author><style face="normal" font="default" size="100%">Vivas-García, Yurena</style></author><author><style face="normal" font="default" size="100%">Torres, Lucia</style></author><author><style face="normal" font="default" size="100%">Ramirez-Jimenez, Laura</style></author><author><style face="normal" font="default" size="100%">Lopez, Yamila</style></author><author><style face="normal" font="default" size="100%">Horrillo, Daniel</style></author><author><style face="normal" font="default" size="100%">Vila-Bedmar, Rocio</style></author><author><style face="normal" font="default" size="100%">Barber-Cano, Eloisa</style></author><author><style face="normal" font="default" size="100%">Izquierdo-Lahuerta, Adriana</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Martínez, Carmen</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Ros, Manuel</style></author><author><style face="normal" font="default" size="100%">Medina-Gomez, Gema</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">microRNAs-mediated regulation of insulin signaling in white adipose tissue during aging: Role of caloric restriction.</style></title><secondary-title><style face="normal" font="default" size="100%">Aging Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Aging Cell</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2023 Jul 04</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">e13919</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Caloric restriction is a non-pharmacological intervention known to ameliorate the metabolic defects associated with aging, including insulin resistance. The levels of miRNA expression may represent a predictive tool for aging-related alterations. In order to investigate the role of miRNAs underlying insulin resistance in adipose tissue during the early stages of aging, 3- and 12-month-old male animals fed ad libitum, and 12-month-old male animals fed with a 20% caloric restricted diet were used. In this work we demonstrate that specific miRNAs may contribute to the impaired insulin-stimulated glucose metabolism specifically in the subcutaneous white adipose tissue, through the regulation of target genes implicated in the insulin signaling cascade. Moreover, the expression of these miRNAs is modified by caloric restriction in middle-aged animals, in accordance with the improvement of the metabolic state. Overall, our work demonstrates that alterations in posttranscriptional gene expression because of miRNAs dysregulation might represent an endogenous mechanism by which insulin response in the subcutaneous fat depot is already affected at middle age. Importantly, caloric restriction could prevent this modulation, demonstrating that certain miRNAs could constitute potential biomarkers of age-related metabolic alterations.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, Carlos S</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco M</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Bostelmann, Gerrit</style></author><author><style face="normal" font="default" size="100%">Martínez-González, L Javier</style></author><author><style face="normal" font="default" size="100%">Muñoyerro-Muñiz, Dolores</style></author><author><style face="normal" font="default" size="100%">Villegas, Román</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Baño, Jesús</style></author><author><style face="normal" font="default" size="100%">Romero-Gómez, Manuel</style></author><author><style face="normal" font="default" size="100%">Lorusso, Nicola</style></author><author><style face="normal" font="default" size="100%">Garcia-León, Javier</style></author><author><style face="normal" font="default" size="100%">Navarro-Marí, Jose M</style></author><author><style face="normal" font="default" size="100%">Camacho-Martinez, Pedro</style></author><author><style face="normal" font="default" size="100%">Merino-Diaz, Laura</style></author><author><style face="normal" font="default" size="100%">Salazar, Adolfo de</style></author><author><style face="normal" font="default" size="100%">Viñuela, Laura</style></author><author><style face="normal" font="default" size="100%">Lepe, Jose A</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival.</style></title><secondary-title><style face="normal" font="default" size="100%">Viruses</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Viruses</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Viral</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Pandemics</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Aug 27</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Torrent-Vernetta, Alba</style></author><author><style face="normal" font="default" size="100%">Gaboli, Mirella</style></author><author><style face="normal" font="default" size="100%">Castillo-Corullón, Silvia</style></author><author><style face="normal" font="default" size="100%">Mondéjar-López, Pedro</style></author><author><style face="normal" font="default" size="100%">Sanz Santiago, Verónica</style></author><author><style face="normal" font="default" size="100%">Costa-Colomer, Jordi</style></author><author><style face="normal" font="default" size="100%">Osona, Borja</style></author><author><style face="normal" font="default" size="100%">Torres-Borrego, Javier</style></author><author><style face="normal" font="default" size="100%">de la Serna-Blázquez, Olga</style></author><author><style face="normal" font="default" size="100%">Bellón Alonso, Sara</style></author><author><style face="normal" font="default" size="100%">Caro Aguilera, Pilar</style></author><author><style face="normal" font="default" size="100%">Gimeno-Díaz de Atauri, Álvaro</style></author><author><style face="normal" font="default" size="100%">Valenzuela Soria, Alfredo</style></author><author><style face="normal" font="default" size="100%">Ayats, Roser</style></author><author><style face="normal" font="default" size="100%">Martin de Vicente, Carlos</style></author><author><style face="normal" font="default" size="100%">Velasco González, Valle</style></author><author><style face="normal" font="default" size="100%">Moure González, José Domingo</style></author><author><style face="normal" font="default" size="100%">Canino Calderín, Elisa María</style></author><author><style face="normal" font="default" size="100%">Pastor-Vivero, María Dolores</style></author><author><style face="normal" font="default" size="100%">Villar Álvarez, María Ángeles</style></author><author><style face="normal" font="default" size="100%">Rovira-Amigo, Sandra</style></author><author><style face="normal" font="default" size="100%">Iglesias Serrano, Ignacio</style></author><author><style face="normal" font="default" size="100%">Díez Izquierdo, Ana</style></author><author><style face="normal" font="default" size="100%">de Mir Messa, Inés</style></author><author><style face="normal" font="default" size="100%">Gartner, Silvia</style></author><author><style face="normal" font="default" size="100%">Navarro, Alexandra</style></author><author><style face="normal" font="default" size="100%">Baz-Redón, Noelia</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Camats-Tarruella, Núria</style></author><author><style face="normal" font="default" size="100%">Fernández-Cancio, Mónica</style></author><author><style face="normal" font="default" size="100%">Rapp, Christina</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Griese, Matthias</style></author><author><style face="normal" font="default" size="100%">Moreno-Galdó, Antonio</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">ChILD-Spain Group</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Incidence and Prevalence of Children's Diffuse Lung Disease in Spain.</style></title><secondary-title><style face="normal" font="default" size="100%">Arch Bronconeumol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Arch Bronconeumol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">22-29</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Children's diffuse lung disease, also known as children's Interstitial Lung Diseases (chILD), are a heterogeneous group of rare diseases with relevant morbidity and mortality, which diagnosis and classification are very complex. Epidemiological data are scarce. The aim of this study was to analyse incidence and prevalence of chILD in Spain.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Multicentre observational prospective study in patients from 0 to 18 years of age with chILD to analyse its incidence and prevalence in Spain, based on data reported in 2018 and 2019.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A total of 381 cases with chILD were notified from 51 paediatric pulmonology units all over Spain, covering the 91.7% of the paediatric population. The average incidence of chILD was 8.18 (CI 95% 6.28-10.48) new cases/million of children per year. The average prevalence of chILD was 46.53 (CI 95% 41.81-51.62) cases/million of children. The age group with the highest prevalence were children under 1 year of age. Different types of disorders were seen in children 2-18 years of age compared with children 0-2 years of age. Most frequent cases were: primary pulmonary interstitial glycogenosis in neonates (17/65), neuroendocrine cell hyperplasia of infancy in infants from 1 to 12 months (44/144), idiopathic pulmonary haemosiderosis in children from 1 to 5 years old (13/74), hypersensitivity pneumonitis in children from 5 to 10 years old (9/51), and scleroderma in older than 10 years old (8/47).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;We found a higher incidence and prevalence of chILD than previously described probably due to greater understanding and increased clinician awareness of these rare diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cruz, Raquel</style></author><author><style face="normal" font="default" size="100%">Almeida, Silvia Diz-de</style></author><author><style face="normal" font="default" size="100%">Heredia, Miguel López</style></author><author><style face="normal" font="default" size="100%">Quintela, Inés</style></author><author><style face="normal" font="default" size="100%">Ceballos, Francisco C</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Lorenzo-Salazar, José M</style></author><author><style face="normal" font="default" size="100%">González-Montelongo, Rafaela</style></author><author><style face="normal" font="default" size="100%">Gago-Domínguez, Manuela</style></author><author><style face="normal" font="default" size="100%">Porras, Marta Sevilla</style></author><author><style face="normal" font="default" size="100%">Castaño, Jair Antonio Tenorio</style></author><author><style face="normal" font="default" size="100%">Nevado, Julián</style></author><author><style face="normal" font="default" size="100%">Aguado, Jose María</style></author><author><style face="normal" font="default" size="100%">Aguilar, Carlos</style></author><author><style face="normal" font="default" size="100%">Aguilera-Albesa, Sergio</style></author><author><style face="normal" font="default" size="100%">Almadana, Virginia</style></author><author><style face="normal" font="default" size="100%">Almoguera, Berta</style></author><author><style face="normal" font="default" size="100%">Alvarez, Nuria</style></author><author><style face="normal" font="default" size="100%">Andreu-Bernabeu, Álvaro</style></author><author><style face="normal" font="default" size="100%">Arana-Arri, Eunate</style></author><author><style face="normal" font="default" size="100%">Arango, Celso</style></author><author><style face="normal" font="default" size="100%">Arranz, María J</style></author><author><style face="normal" font="default" size="100%">Artiga, Maria-Jesus</style></author><author><style face="normal" font="default" size="100%">Baptista-Rosas, Raúl C</style></author><author><style face="normal" font="default" size="100%">Barreda-Sánchez, María</style></author><author><style face="normal" font="default" size="100%">Belhassen-Garcia, Moncef</style></author><author><style face="normal" font="default" size="100%">Bezerra, Joao F</style></author><author><style face="normal" font="default" size="100%">Bezerra, Marcos A C</style></author><author><style face="normal" font="default" size="100%">Boix-Palop, Lucía</style></author><author><style face="normal" font="default" size="100%">Brión, Maria</style></author><author><style face="normal" font="default" size="100%">Brugada, Ramón</style></author><author><style face="normal" font="default" size="100%">Bustos, Matilde</style></author><author><style face="normal" font="default" size="100%">Calderón, Enrique J</style></author><author><style face="normal" font="default" size="100%">Carbonell, Cristina</style></author><author><style face="normal" font="default" size="100%">Castano, Luis</style></author><author><style face="normal" font="default" size="100%">Castelao, Jose E</style></author><author><style face="normal" font="default" size="100%">Conde-Vicente, Rosa</style></author><author><style face="normal" font="default" size="100%">Cordero-Lorenzana, M Lourdes</style></author><author><style face="normal" font="default" size="100%">Cortes-Sanchez, Jose L</style></author><author><style face="normal" font="default" size="100%">Corton, Marta</style></author><author><style face="normal" font="default" size="100%">Darnaude, M Teresa</style></author><author><style face="normal" font="default" size="100%">De Martino-Rodríguez, Alba</style></author><author><style face="normal" font="default" size="100%">Campo-Pérez, Victor</style></author><author><style face="normal" font="default" size="100%">Bustamante, Aranzazu Diaz</style></author><author><style face="normal" font="default" size="100%">Domínguez-Garrido, Elena</style></author><author><style face="normal" font="default" size="100%">Luchessi, André D</style></author><author><style face="normal" font="default" size="100%">Eirós, Rocío</style></author><author><style face="normal" font="default" size="100%">Sanabria, Gladys Mercedes Estigarribia</style></author><author><style face="normal" font="default" size="100%">Fariñas, María Carmen</style></author><author><style face="normal" font="default" size="100%">Fernández-Robelo, Uxía</style></author><author><style face="normal" font="default" size="100%">Fernández-Rodríguez, Amanda</style></author><author><style face="normal" font="default" size="100%">Fernández-Villa, Tania</style></author><author><style face="normal" font="default" size="100%">Gil-Fournier, Belén</style></author><author><style face="normal" font="default" size="100%">Gómez-Arrue, Javier</style></author><author><style face="normal" font="default" size="100%">Álvarez, Beatriz González</style></author><author><style face="normal" font="default" size="100%">Quirós, Fernan Gonzalez Bernaldo</style></author><author><style face="normal" font="default" size="100%">González-Peñas, Javier</style></author><author><style face="normal" font="default" size="100%">Gutiérrez-Bautista, Juan F</style></author><author><style face="normal" font="default" size="100%">Herrero, María José</style></author><author><style face="normal" font="default" size="100%">Herrero-Gonzalez, Antonio</style></author><author><style face="normal" font="default" size="100%">Jimenez-Sousa, María A</style></author><author><style face="normal" font="default" size="100%">Lattig, María Claudia</style></author><author><style face="normal" font="default" size="100%">Borja, Anabel Liger</style></author><author><style face="normal" font="default" size="100%">Lopez-Rodriguez, Rosario</style></author><author><style face="normal" font="default" size="100%">Mancebo, Esther</style></author><author><style face="normal" font="default" size="100%">Martín-López, Caridad</style></author><author><style face="normal" font="default" size="100%">Martín, Vicente</style></author><author><style face="normal" font="default" size="100%">Martinez-Nieto, Oscar</style></author><author><style face="normal" font="default" size="100%">Martinez-Lopez, Iciar</style></author><author><style face="normal" font="default" size="100%">Martinez-Resendez, Michel F</style></author><author><style face="normal" font="default" size="100%">Martinez-Perez, Ángel</style></author><author><style face="normal" font="default" size="100%">Mazzeu, Juliana A</style></author><author><style face="normal" font="default" size="100%">Macías, Eleuterio Merayo</style></author><author><style face="normal" font="default" size="100%">Minguez, Pablo</style></author><author><style face="normal" font="default" size="100%">Cuerda, Victor Moreno</style></author><author><style face="normal" font="default" size="100%">Silbiger, Vivian N</style></author><author><style face="normal" font="default" size="100%">Oliveira, Silviene F</style></author><author><style face="normal" font="default" size="100%">Ortega-Paino, Eva</style></author><author><style face="normal" font="default" size="100%">Parellada, Mara</style></author><author><style face="normal" font="default" size="100%">Paz-Artal, Estela</style></author><author><style face="normal" font="default" size="100%">Santos, Ney P C</style></author><author><style face="normal" font="default" size="100%">Pérez-Matute, Patricia</style></author><author><style face="normal" font="default" size="100%">Perez, Patricia</style></author><author><style face="normal" font="default" size="100%">Pérez-Tomás, M Elena</style></author><author><style face="normal" font="default" size="100%">Perucho, Teresa</style></author><author><style face="normal" font="default" size="100%">Pinsach-Abuin, Mel Lina</style></author><author><style face="normal" font="default" size="100%">Pompa-Mera, Ericka N</style></author><author><style face="normal" font="default" size="100%">Porras-Hurtado, Gloria L</style></author><author><style face="normal" font="default" size="100%">Pujol, Aurora</style></author><author><style face="normal" font="default" size="100%">León, Soraya Ramiro</style></author><author><style face="normal" font="default" size="100%">Resino, Salvador</style></author><author><style face="normal" font="default" size="100%">Fernandes, Marianne R</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Ruiz, Emilio</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Artalejo, Fernando</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Garcia, José A</style></author><author><style face="normal" font="default" size="100%">Ruiz-Cabello, Francisco</style></author><author><style face="normal" font="default" size="100%">Ruiz-Hornillos, Javier</style></author><author><style face="normal" font="default" size="100%">Ryan, Pablo</style></author><author><style face="normal" font="default" size="100%">Soria, José Manuel</style></author><author><style face="normal" font="default" size="100%">Souto, Juan Carlos</style></author><author><style face="normal" font="default" size="100%">Tamayo, Eduardo</style></author><author><style face="normal" font="default" size="100%">Tamayo-Velasco, Alvaro</style></author><author><style face="normal" font="default" size="100%">Taracido-Fernandez, Juan Carlos</style></author><author><style face="normal" font="default" size="100%">Teper, Alejandro</style></author><author><style face="normal" font="default" size="100%">Torres-Tobar, Lilian</style></author><author><style face="normal" font="default" size="100%">Urioste, Miguel</style></author><author><style face="normal" font="default" size="100%">Valencia-Ramos, Juan</style></author><author><style face="normal" font="default" size="100%">Yáñez, Zuleima</style></author><author><style face="normal" font="default" size="100%">Zarate, Ruth</style></author><author><style face="normal" font="default" size="100%">Nakanishi, Tomoko</style></author><author><style face="normal" font="default" size="100%">Pigazzini, Sara</style></author><author><style face="normal" font="default" size="100%">Degenhardt, Frauke</style></author><author><style face="normal" font="default" size="100%">Butler-Laporte, Guillaume</style></author><author><style face="normal" font="default" size="100%">Maya-Miles, Douglas</style></author><author><style face="normal" font="default" size="100%">Bujanda, Luis</style></author><author><style face="normal" font="default" size="100%">Bouysran, Youssef</style></author><author><style face="normal" font="default" size="100%">Palom, Adriana</style></author><author><style face="normal" font="default" size="100%">Ellinghaus, David</style></author><author><style face="normal" font="default" size="100%">Martínez-Bueno, Manuel</style></author><author><style face="normal" font="default" size="100%">Rolker, Selina</style></author><author><style face="normal" font="default" size="100%">Amitrano, Sara</style></author><author><style face="normal" font="default" size="100%">Roade, Luisa</style></author><author><style face="normal" font="default" size="100%">Fava, Francesca</style></author><author><style face="normal" font="default" size="100%">Spinner, Christoph D</style></author><author><style face="normal" font="default" size="100%">Prati, Daniele</style></author><author><style face="normal" font="default" size="100%">Bernardo, David</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author><author><style face="normal" font="default" size="100%">Darcis, Gilles</style></author><author><style face="normal" font="default" size="100%">Fernández-Cadenas, Israel</style></author><author><style face="normal" font="default" size="100%">Holter, Jan Cato</style></author><author><style face="normal" font="default" size="100%">Banales, Jesus M</style></author><author><style face="normal" font="default" size="100%">Frithiof, Robert</style></author><author><style face="normal" font="default" size="100%">Duga, Stefano</style></author><author><style face="normal" font="default" size="100%">Asselta, Rosanna</style></author><author><style face="normal" font="default" size="100%">Pereira, Alexandre C</style></author><author><style face="normal" font="default" size="100%">Romero-Gómez, Manuel</style></author><author><style face="normal" font="default" size="100%">Nafría-Jiménez, Beatriz</style></author><author><style face="normal" font="default" size="100%">Hov, Johannes R</style></author><author><style face="normal" font="default" size="100%">Migeotte, Isabelle</style></author><author><style face="normal" font="default" size="100%">Renieri, Alessandra</style></author><author><style face="normal" font="default" size="100%">Planas, Anna M</style></author><author><style face="normal" font="default" size="100%">Ludwig, Kerstin U</style></author><author><style face="normal" font="default" size="100%">Buti, Maria</style></author><author><style face="normal" font="default" size="100%">Rahmouni, Souad</style></author><author><style face="normal" font="default" size="100%">Alarcón-Riquelme, Marta E</style></author><author><style face="normal" font="default" size="100%">Schulte, Eva C</style></author><author><style face="normal" font="default" size="100%">Franke, Andre</style></author><author><style face="normal" font="default" size="100%">Karlsen, Tom H</style></author><author><style face="normal" font="default" size="100%">Valenti, Luca</style></author><author><style face="normal" font="default" size="100%">Zeberg, Hugo</style></author><author><style face="normal" font="default" size="100%">Richards, Brent</style></author><author><style face="normal" font="default" size="100%">Ganna, Andrea</style></author><author><style face="normal" font="default" size="100%">Boada, Mercè</style></author><author><style face="normal" font="default" size="100%">Rojas, Itziar</style></author><author><style face="normal" font="default" size="100%">Ruiz, Agustín</style></author><author><style face="normal" font="default" size="100%">Sánchez, Pascual</style></author><author><style face="normal" font="default" size="100%">Real, Luis Miguel</style></author><author><style face="normal" font="default" size="100%">Guillén-Navarro, Encarna</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author><author><style face="normal" font="default" size="100%">González-Neira, Anna</style></author><author><style face="normal" font="default" size="100%">Riancho, José A</style></author><author><style face="normal" font="default" size="100%">Rojas-Martinez, Augusto</style></author><author><style face="normal" font="default" size="100%">Flores, Carlos</style></author><author><style face="normal" font="default" size="100%">Lapunzina, Pablo</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">SCOURGE Cohort Group</style></author><author><style face="normal" font="default" size="100%">HOSTAGE Cohort Group</style></author><author><style face="normal" font="default" size="100%">GRA@CE Cohort Group</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Novel genes and sex differences in COVID-19 severity.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Jun 16</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Here we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p &lt; 5x10-8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10-22 and p = 8.1x10-12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10-8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10-8) and ARHGAP33 (p = 1.3x10-8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10-8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (&lt;60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Olivares-González, Lorena</style></author><author><style face="normal" font="default" size="100%">Velasco, Sheyla</style></author><author><style face="normal" font="default" size="100%">Gallego, Idoia</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Puras, Gustavo</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Martínez-Romero, Alicia</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Pedraz, José Luis</style></author><author><style face="normal" font="default" size="100%">Rodrigo, Regina</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An SPM-Enriched Marine Oil Supplement Shifted Microglia Polarization toward M2, Ameliorating Retinal Degeneration in  Mice.</style></title><secondary-title><style face="normal" font="default" size="100%">Antioxidants (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Antioxidants (Basel)</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Dec 30</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy causing progressive vision loss. It is accompanied by chronic and sustained inflammation, including M1 microglia activation. This study evaluated the effect of an essential fatty acid (EFA) supplement containing specialized pro-resolving mediators (SPMs), on retinal degeneration and microglia activation in  mice, a model of RP, as well as on LPS-stimulated BV2 cells. The EFA supplement was orally administered to mice from postnatal day (P)9 to P18. At P18, the electrical activity of the retina was examined by electroretinography (ERG) and innate behavior in response to light were measured. Retinal degeneration was studied via histology including the TUNEL assay and microglia immunolabeling. Microglia polarization (M1/M2) was assessed by flow cytometry, qPCR, ELISA and histology. Redox status was analyzed by measuring antioxidant enzymes and markers of oxidative damage. Interestingly, the EFA supplement ameliorated retinal dysfunction and degeneration by improving ERG recording and sensitivity to light, and reducing photoreceptor cell loss. The EFA supplement reduced inflammation and microglia activation attenuating M1 markers as well as inducing a shift to the M2 phenotype in  mouse retinas and LPS-stimulated BV2 cells. It also reduced oxidative stress markers of lipid peroxidation and carbonylation. These findings could open up new therapeutic opportunities based on resolving inflammation with oral supplementation with SPMs such as the EFA supplement.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ostaszewski, Marek</style></author><author><style face="normal" font="default" size="100%">Niarakis, Anna</style></author><author><style face="normal" font="default" size="100%">Mazein, Alexander</style></author><author><style face="normal" font="default" size="100%">Kuperstein, Inna</style></author><author><style face="normal" font="default" size="100%">Phair, Robert</style></author><author><style face="normal" font="default" size="100%">Orta-Resendiz, Aurelio</style></author><author><style face="normal" font="default" size="100%">Singh, Vidisha</style></author><author><style face="normal" font="default" size="100%">Aghamiri, Sara Sadat</style></author><author><style face="normal" font="default" size="100%">Acencio, Marcio Luis</style></author><author><style face="normal" font="default" size="100%">Glaab, Enrico</style></author><author><style face="normal" font="default" size="100%">Ruepp, Andreas</style></author><author><style face="normal" font="default" size="100%">Fobo, Gisela</style></author><author><style face="normal" font="default" size="100%">Montrone, Corinna</style></author><author><style face="normal" font="default" size="100%">Brauner, Barbara</style></author><author><style face="normal" font="default" size="100%">Frishman, Goar</style></author><author><style face="normal" font="default" size="100%">Monraz Gómez, Luis Cristóbal</style></author><author><style face="normal" font="default" size="100%">Somers, Julia</style></author><author><style face="normal" font="default" size="100%">Hoch, Matti</style></author><author><style face="normal" font="default" size="100%">Kumar Gupta, Shailendra</style></author><author><style face="normal" font="default" size="100%">Scheel, Julia</style></author><author><style face="normal" font="default" size="100%">Borlinghaus, Hanna</style></author><author><style face="normal" font="default" size="100%">Czauderna, Tobias</style></author><author><style face="normal" font="default" size="100%">Schreiber, Falk</style></author><author><style face="normal" font="default" size="100%">Montagud, Arnau</style></author><author><style face="normal" font="default" size="100%">Ponce de Leon, Miguel</style></author><author><style face="normal" font="default" size="100%">Funahashi, Akira</style></author><author><style face="normal" font="default" size="100%">Hiki, Yusuke</style></author><author><style face="normal" font="default" size="100%">Hiroi, Noriko</style></author><author><style face="normal" font="default" size="100%">Yamada, Takahiro G</style></author><author><style face="normal" font="default" size="100%">Dräger, Andreas</style></author><author><style face="normal" font="default" size="100%">Renz, Alina</style></author><author><style face="normal" font="default" size="100%">Naveez, Muhammad</style></author><author><style face="normal" font="default" size="100%">Bocskei, Zsolt</style></author><author><style face="normal" font="default" size="100%">Messina, Francesco</style></author><author><style face="normal" font="default" size="100%">Börnigen, Daniela</style></author><author><style face="normal" font="default" size="100%">Fergusson, Liam</style></author><author><style face="normal" font="default" size="100%">Conti, Marta</style></author><author><style face="normal" font="default" size="100%">Rameil, Marius</style></author><author><style face="normal" font="default" size="100%">Nakonecnij, Vanessa</style></author><author><style face="normal" font="default" size="100%">Vanhoefer, Jakob</style></author><author><style face="normal" font="default" size="100%">Schmiester, Leonard</style></author><author><style face="normal" font="default" size="100%">Wang, Muying</style></author><author><style face="normal" font="default" size="100%">Ackerman, Emily E</style></author><author><style face="normal" font="default" size="100%">Shoemaker, Jason E</style></author><author><style face="normal" font="default" size="100%">Zucker, Jeremy</style></author><author><style face="normal" font="default" size="100%">Oxford, Kristie</style></author><author><style face="normal" font="default" size="100%">Teuton, Jeremy</style></author><author><style face="normal" font="default" size="100%">Kocakaya, Ebru</style></author><author><style face="normal" font="default" size="100%">Summak, Gökçe Yağmur</style></author><author><style face="normal" font="default" size="100%">Hanspers, Kristina</style></author><author><style face="normal" font="default" size="100%">Kutmon, Martina</style></author><author><style face="normal" font="default" size="100%">Coort, Susan</style></author><author><style face="normal" font="default" size="100%">Eijssen, Lars</style></author><author><style face="normal" font="default" size="100%">Ehrhart, Friederike</style></author><author><style face="normal" font="default" size="100%">Rex, Devasahayam Arokia Balaya</style></author><author><style face="normal" font="default" size="100%">Slenter, Denise</style></author><author><style face="normal" font="default" size="100%">Martens, Marvin</style></author><author><style face="normal" font="default" size="100%">Pham, Nhung</style></author><author><style face="normal" font="default" size="100%">Haw, Robin</style></author><author><style face="normal" font="default" size="100%">Jassal, Bijay</style></author><author><style face="normal" font="default" size="100%">Matthews, Lisa</style></author><author><style face="normal" font="default" size="100%">Orlic-Milacic, Marija</style></author><author><style face="normal" font="default" size="100%">Senff Ribeiro, Andrea</style></author><author><style face="normal" font="default" size="100%">Rothfels, Karen</style></author><author><style face="normal" font="default" size="100%">Shamovsky, Veronica</style></author><author><style face="normal" font="default" size="100%">Stephan, Ralf</style></author><author><style face="normal" font="default" size="100%">Sevilla, Cristoffer</style></author><author><style face="normal" font="default" size="100%">Varusai, Thawfeek</style></author><author><style face="normal" font="default" size="100%">Ravel, Jean-Marie</style></author><author><style face="normal" font="default" size="100%">Fraser, Rupsha</style></author><author><style face="normal" font="default" size="100%">Ortseifen, Vera</style></author><author><style face="normal" font="default" size="100%">Marchesi, Silvia</style></author><author><style face="normal" font="default" size="100%">Gawron, Piotr</style></author><author><style face="normal" font="default" size="100%">Smula, Ewa</style></author><author><style face="normal" font="default" size="100%">Heirendt, Laurent</style></author><author><style face="normal" font="default" size="100%">Satagopam, Venkata</style></author><author><style face="normal" font="default" size="100%">Wu, Guanming</style></author><author><style face="normal" font="default" size="100%">Riutta, Anders</style></author><author><style face="normal" font="default" size="100%">Golebiewski, Martin</style></author><author><style face="normal" font="default" size="100%">Owen, Stuart</style></author><author><style face="normal" font="default" size="100%">Goble, Carole</style></author><author><style face="normal" font="default" size="100%">Hu, Xiaoming</style></author><author><style face="normal" font="default" size="100%">Overall, Rupert W</style></author><author><style face="normal" font="default" size="100%">Maier, Dieter</style></author><author><style face="normal" font="default" size="100%">Bauch, Angela</style></author><author><style face="normal" font="default" size="100%">Gyori, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Bachman, John A</style></author><author><style face="normal" font="default" size="100%">Vega, Carlos</style></author><author><style face="normal" font="default" size="100%">Grouès, Valentin</style></author><author><style face="normal" font="default" size="100%">Vazquez, Miguel</style></author><author><style face="normal" font="default" size="100%">Porras, Pablo</style></author><author><style face="normal" font="default" size="100%">Licata, Luana</style></author><author><style face="normal" font="default" size="100%">Iannuccelli, Marta</style></author><author><style face="normal" font="default" size="100%">Sacco, Francesca</style></author><author><style face="normal" font="default" size="100%">Nesterova, Anastasia</style></author><author><style face="normal" font="default" size="100%">Yuryev, Anton</style></author><author><style face="normal" font="default" size="100%">de Waard, Anita</style></author><author><style face="normal" font="default" size="100%">Turei, Denes</style></author><author><style face="normal" font="default" size="100%">Luna, Augustin</style></author><author><style face="normal" font="default" size="100%">Babur, Ozgun</style></author><author><style face="normal" font="default" size="100%">Soliman, Sylvain</style></author><author><style face="normal" font="default" size="100%">Valdeolivas, Alberto</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Helikar, Tomáš</style></author><author><style face="normal" font="default" size="100%">Puniya, Bhanwar Lal</style></author><author><style face="normal" font="default" size="100%">Modos, Dezso</style></author><author><style face="normal" font="default" size="100%">Treveil, Agatha</style></author><author><style face="normal" font="default" size="100%">Olbei, Marton</style></author><author><style face="normal" font="default" size="100%">De Meulder, Bertrand</style></author><author><style face="normal" font="default" size="100%">Ballereau, Stephane</style></author><author><style face="normal" font="default" size="100%">Dugourd, Aurélien</style></author><author><style face="normal" font="default" size="100%">Naldi, Aurélien</style></author><author><style face="normal" font="default" size="100%">Noël, Vincent</style></author><author><style face="normal" font="default" size="100%">Calzone, Laurence</style></author><author><style face="normal" font="default" size="100%">Sander, Chris</style></author><author><style face="normal" font="default" size="100%">Demir, Emek</style></author><author><style face="normal" font="default" size="100%">Korcsmaros, Tamas</style></author><author><style face="normal" font="default" size="100%">Freeman, Tom C</style></author><author><style face="normal" font="default" size="100%">Augé, Franck</style></author><author><style face="normal" font="default" size="100%">Beckmann, Jacques S</style></author><author><style face="normal" font="default" size="100%">Hasenauer, Jan</style></author><author><style face="normal" font="default" size="100%">Wolkenhauer, Olaf</style></author><author><style face="normal" font="default" size="100%">Wilighagen, Egon L</style></author><author><style face="normal" font="default" size="100%">Pico, Alexander R</style></author><author><style face="normal" font="default" size="100%">Evelo, Chris T</style></author><author><style face="normal" font="default" size="100%">Gillespie, Marc E</style></author><author><style face="normal" font="default" size="100%">Stein, Lincoln D</style></author><author><style face="normal" font="default" size="100%">Hermjakob, Henning</style></author><author><style face="normal" font="default" size="100%">D'Eustachio, Peter</style></author><author><style face="normal" font="default" size="100%">Saez-Rodriguez, Julio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Valencia, Alfonso</style></author><author><style face="normal" font="default" size="100%">Kitano, Hiroaki</style></author><author><style face="normal" font="default" size="100%">Barillot, Emmanuel</style></author><author><style face="normal" font="default" size="100%">Auffray, Charles</style></author><author><style face="normal" font="default" size="100%">Balling, Rudi</style></author><author><style face="normal" font="default" size="100%">Schneider, Reinhard</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">COVID-19 Disease Map Community</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Syst Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Syst Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antiviral Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Graphics</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytokines</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Mining</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Host Microbial Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Immunity, Cellular</style></keyword><keyword><style  face="normal" font="default" size="100%">Immunity, Humoral</style></keyword><keyword><style  face="normal" font="default" size="100%">Immunity, Innate</style></keyword><keyword><style  face="normal" font="default" size="100%">Lymphocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolic Networks and Pathways</style></keyword><keyword><style  face="normal" font="default" size="100%">Myeloid Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Interaction Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Viral Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 10</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">e10387</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/34664389?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Roldán, Gema</style></author><author><style face="normal" font="default" size="100%">Perez-Florido, Javier</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco M</style></author><author><style face="normal" font="default" size="100%">Carmona, Rosario</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">López-López, Daniel</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Fernandez-Rueda, Jose L</style></author><author><style face="normal" font="default" size="100%">Gallego, Asunción</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">González-Neira, Anna</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Núñez-Torres, Rocío</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author><author><style face="normal" font="default" size="100%">Minguez, Pablo</style></author><author><style face="normal" font="default" size="100%">Avila-Fernandez, Almudena</style></author><author><style face="normal" font="default" size="100%">Corton, Marta</style></author><author><style face="normal" font="default" size="100%">Moreno-Pelayo, Miguel Ángel</style></author><author><style face="normal" font="default" size="100%">Morin, Matías</style></author><author><style face="normal" font="default" size="100%">Gallego-Martinez, Alvaro</style></author><author><style face="normal" font="default" size="100%">Lopez-Escamez, Jose A</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Amigo, Jorge</style></author><author><style face="normal" font="default" size="100%">Salgado-Garrido, Josefa</style></author><author><style face="normal" font="default" size="100%">Pasalodos-Sanchez, Sara</style></author><author><style face="normal" font="default" size="100%">Morte, Beatriz</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Alonso, Ángel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Spanish Exome Crowdsourcing Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">CSVS, a crowdsourcing database of the Spanish population genetic variability.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Crowdsourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 01 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">D1130-D1137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">D1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32990755?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martinez-Delgado, Beatriz</style></author><author><style face="normal" font="default" size="100%">Lopez-Martin, Estrella</style></author><author><style face="normal" font="default" size="100%">Lara-Herguedas, Julián</style></author><author><style face="normal" font="default" size="100%">Monzon, Sara</style></author><author><style face="normal" font="default" size="100%">Cuesta, Isabel</style></author><author><style face="normal" font="default" size="100%">Juliá, Miguel</style></author><author><style face="normal" font="default" size="100%">Aquino, Virginia</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Martin, Carlos</style></author><author><style face="normal" font="default" size="100%">Damian, Alejandra</style></author><author><style face="normal" font="default" size="100%">Gonzalo, Irene</style></author><author><style face="normal" font="default" size="100%">Gomez-Mariano, Gema</style></author><author><style face="normal" font="default" size="100%">Baladron, Beatriz</style></author><author><style face="normal" font="default" size="100%">Cazorla, Rosario</style></author><author><style face="normal" font="default" size="100%">Iglesias, Gema</style></author><author><style face="normal" font="default" size="100%">Roman, Enriqueta</style></author><author><style face="normal" font="default" size="100%">Ros, Purificacion</style></author><author><style face="normal" font="default" size="100%">Tutor, Pablo</style></author><author><style face="normal" font="default" size="100%">Mellor, Susana</style></author><author><style face="normal" font="default" size="100%">Jimenez, Carlos</style></author><author><style face="normal" font="default" size="100%">Cabrejas, Maria Jose</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Vioque, Emiliano</style></author><author><style face="normal" font="default" size="100%">Alonso, Javier</style></author><author><style face="normal" font="default" size="100%">Bermejo-Sánchez, Eva</style></author><author><style face="normal" font="default" size="100%">Posada, Manuel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">De novo small deletion affecting transcription start site of short isoform of AUTS2 gene in a patient with syndromic neurodevelopmental defects.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytoskeletal Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Dwarfism</style></keyword><keyword><style  face="normal" font="default" size="100%">Exons</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurodevelopmental Disorders</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Isoforms</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Deletion</style></keyword><keyword><style  face="normal" font="default" size="100%">Syndrome</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Initiation Site</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">185</style></volume><pages><style face="normal" font="default" size="100%">877-883</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Disruption of the autism susceptibility candidate 2 (AUTS2) gene through genomic rearrangements, copy number variations (CNVs), and intragenic deletions and mutations, has been recurrently involved in syndromic forms of developmental delay and intellectual disability, known as AUTS2 syndrome. The AUTS2 gene plays an important role in regulation of neuronal migration, and when altered, associates with a variable phenotype from severely to mildly affected patients. The more severe phenotypes significantly correlate with the presence of defects affecting the C-terminus part of the gene. This article reports a new patient with a syndromic neurodevelopmental disorder, who presents a deletion of 30 nucleotides in the exon 9 of the AUTS2 gene. Importantly, this deletion includes the transcription start site for the AUTS2 short transcript isoform, which has an important role in brain development. Gene expression analysis of AUTS2 full-length and short isoforms revealed that the deletion found in this patient causes a remarkable reduction in the expression level, not only of the short isoform, but also of the full AUTS2 transcripts. This report adds more evidence for the role of mutated AUTS2 short transcripts in the development of a severe phenotype in the AUTS2 syndrome.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Cordero Varela, Juan Antonio</style></author><author><style face="normal" font="default" size="100%">Alvarez-Alegret, Ramiro</style></author><author><style face="normal" font="default" size="100%">Agra-Pujol, Carolina</style></author><author><style face="normal" font="default" size="100%">Izquierdo, Francisco</style></author><author><style face="normal" font="default" size="100%">Ramos, Rafael</style></author><author><style face="normal" font="default" size="100%">Ortega-Medina, Luis</style></author><author><style face="normal" font="default" size="100%">Martin-Davila, Francisco</style></author><author><style face="normal" font="default" size="100%">Castilla-Ramirez, Carolina</style></author><author><style face="normal" font="default" size="100%">Hernandez-Leon, Carmen Nieves</style></author><author><style face="normal" font="default" size="100%">Romagosa, Cleofe</style></author><author><style face="normal" font="default" size="100%">Vaz Salgado, Maria Angeles</style></author><author><style face="normal" font="default" size="100%">Lavernia, Javier</style></author><author><style face="normal" font="default" size="100%">Bagué, Silvia</style></author><author><style face="normal" font="default" size="100%">Mayodormo-Aranda, Empar</style></author><author><style face="normal" font="default" size="100%">Vicioso, Luis</style></author><author><style face="normal" font="default" size="100%">Hernández Barceló, Jose Emilio</style></author><author><style face="normal" font="default" size="100%">Rubio-Casadevall, Jordi</style></author><author><style face="normal" font="default" size="100%">de Juan, Ana</style></author><author><style face="normal" font="default" size="100%">Fiaño-Valverde, Maria Concepcion</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Lopez-Alvarez, Maria</style></author><author><style face="normal" font="default" size="100%">Lacerenza, Serena</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Gutierrez, Antonio</style></author><author><style face="normal" font="default" size="100%">Alvarez, Rosa</style></author><author><style face="normal" font="default" size="100%">Valverde, Claudia</style></author><author><style face="normal" font="default" size="100%">Martinez-Trufero, Javier</style></author><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A DNA damage repair gene-associated signature predicts responses of patients with advanced soft-tissue sarcoma to treatment with trabectedin.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Oncol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Oncol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">3691-3705</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Predictive biomarkers of trabectedin represent an unmet need in advanced soft-tissue sarcomas (STS). DNA damage repair (DDR) genes, involved in homologous recombination or nucleotide excision repair, had been previously described as biomarkers of trabectedin resistance or sensitivity, respectively. The majority of these studies only focused on specific factors (ERCC1, ERCC5, and BRCA1) and did not evaluate several other DDR-related genes that could have a relevant role for trabectedin efficacy. In this retrospective translational study, 118 genes involved in DDR were evaluated to determine, by transcriptomics, a predictive gene signature of trabectedin efficacy. A six-gene predictive signature of trabectedin efficacy was built in a series of 139 tumor samples from patients with advanced STS. Patients in the high-risk gene signature group showed a significantly worse progression-free survival compared with patients in the low-risk group (2.1 vs 6.0 months, respectively). Differential gene expression analysis defined new potential predictive biomarkers of trabectedin sensitivity (PARP3 and CCNH) or resistance (DNAJB11 and PARP1). Our study identified a new gene signature that significantly predicts patients with higher probability to respond to treatment with trabectedin. Targeting some genes of this signature emerges as a potential strategy to enhance trabectedin efficacy.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33983674?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R.</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Falco, Matias M.</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Alamo-Alvarez, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data</style></title><secondary-title><style face="normal" font="default" size="100%">Computational and Structural Biotechnology Journal</style></secondary-title><short-title><style face="normal" font="default" size="100%">Computational and Structural Biotechnology Journal</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-01-2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://linkinghub.elsevier.com/retrieve/pii/S2001037021002038</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2968 - 2978</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Maya-Miles, Douglas</style></author><author><style face="normal" font="default" size="100%">García, Federico</style></author><author><style face="normal" font="default" size="100%">Lorusso, Nicola</style></author><author><style face="normal" font="default" size="100%">Calleja, Miguel Ángel</style></author><author><style face="normal" font="default" size="100%">Pareja, María Jesús</style></author><author><style face="normal" font="default" size="100%">López-Miranda, José</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Baño, Jesús</style></author><author><style face="normal" font="default" size="100%">Padillo, Javier</style></author><author><style face="normal" font="default" size="100%">Túnez, Isaac</style></author><author><style face="normal" font="default" size="100%">Romero-Gómez, Manuel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System.</style></title><secondary-title><style face="normal" font="default" size="100%">J Pers Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Pers Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 May 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The COVID-19 pandemic represents an unprecedented opportunity to exploit the advantages of personalized medicine for the prevention, diagnosis, treatment, surveillance and management of a new challenge in public health. COVID-19 infection is highly variable, ranging from asymptomatic infections to severe, life-threatening manifestations. Personalized medicine can play a key role in elucidating individual susceptibility to the infection as well as inter-individual variability in clinical course, prognosis and response to treatment. Integrating personalized medicine into clinical practice can also transform health care by enabling the design of preventive and therapeutic strategies tailored to individual profiles, improving the detection of outbreaks or defining transmission patterns at an increasingly local level. SARS-CoV2 genome sequencing, together with the assessment of specific patient genetic variants, will support clinical decision-makers and ultimately better ways to fight this disease. Additionally, it would facilitate a better stratification and selection of patients for clinical trials, thus increasing the likelihood of obtaining positive results. Lastly, defining a national strategy to implement in clinical practice all available tools of personalized medicine in COVID-19 could be challenging but linked to a positive transformation of the health care system. In this review, we provide an update of the achievements, promises, and challenges of personalized medicine in the fight against COVID-19 from susceptibility to natural history and response to therapy, as well as from surveillance to control measures and vaccination. We also discuss strategies to facilitate the adoption of this new paradigm for medical and public health measures during and after the pandemic in health care systems.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/34073493?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Falco, Matias M</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Gunyel, Devrim</style></author><author><style face="normal" font="default" size="100%">Ostaszewski, Marek</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mechanistic modeling of the SARS-CoV-2 disease map.</style></title><secondary-title><style face="normal" font="default" size="100%">BioData Min</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BioData Min</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Jan 21</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33478554?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Millán-Esteban, David</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">García-Casado, Zaida</style></author><author><style face="normal" font="default" size="100%">Manrique-Silva, Esperanza</style></author><author><style face="normal" font="default" size="100%">Requena, Celia</style></author><author><style face="normal" font="default" size="100%">Bañuls, José</style></author><author><style face="normal" font="default" size="100%">Lopez-Guerrero, Jose Antonio</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Hernández, Aranzazu</style></author><author><style face="normal" font="default" size="100%">Traves, Víctor</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Virós, Amaya</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajiv</style></author><author><style face="normal" font="default" size="100%">Nagore, Eduardo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development.</style></title><secondary-title><style face="normal" font="default" size="100%">Cancers (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cancers (Basel)</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Oct 18</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;According to the divergent pathway model, cutaneous melanoma comprises a nevogenic group with a propensity to melanocyte proliferation and another one associated with cumulative solar damage (CSD). While characterized clinically and epidemiologically, the differences in the molecular profiles between the groups have remained primarily uninvestigated. This study has used a custom gene panel and bioinformatics tools to investigate the potential molecular differences in a thoroughly characterized cohort of 119 melanoma patients belonging to nevogenic and CSD groups. We found that the nevogenic melanomas had a restricted set of mutations, with the prominently mutated gene being . The CSD melanomas, in contrast, showed mutations in a diverse group of genes that included , , , and . We thus provide evidence that nevogenic and CSD melanomas constitute different biological entities and highlight the need to explore new targeted therapies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">20</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Heath, Allison P.</style></author><author><style face="normal" font="default" size="100%">Ferretti, Vincent</style></author><author><style face="normal" font="default" size="100%">Agrawal, Stuti</style></author><author><style face="normal" font="default" size="100%">An, Maksim</style></author><author><style face="normal" font="default" size="100%">Angelakos, James C.</style></author><author><style face="normal" font="default" size="100%">Arya, Renuka</style></author><author><style face="normal" font="default" size="100%">Bajari, Rosita</style></author><author><style face="normal" font="default" size="100%">Baqar, Bilal</style></author><author><style face="normal" font="default" size="100%">Barnowski, Justin H. B.</style></author><author><style face="normal" font="default" size="100%">Burt, Jeffrey</style></author><author><style face="normal" font="default" size="100%">Catton, Ann</style></author><author><style face="normal" font="default" size="100%">Chan, Brandon F.</style></author><author><style face="normal" font="default" size="100%">Chu, Fay</style></author><author><style face="normal" font="default" size="100%">Cullion, Kim</style></author><author><style face="normal" font="default" size="100%">Davidsen, Tanja</style></author><author><style face="normal" font="default" size="100%">Do, Phuong-My</style></author><author><style face="normal" font="default" size="100%">Dompierre, Christian</style></author><author><style face="normal" font="default" size="100%">Ferguson, Martin L.</style></author><author><style face="normal" font="default" size="100%">Fitzsimons, Michael S.</style></author><author><style face="normal" font="default" size="100%">Ford, Michael</style></author><author><style face="normal" font="default" size="100%">Fukuma, Miyuki</style></author><author><style face="normal" font="default" size="100%">Gaheen, Sharon</style></author><author><style face="normal" font="default" size="100%">Ganji, Gajanan L.</style></author><author><style face="normal" font="default" size="100%">Garcia, Tzintzuni I.</style></author><author><style face="normal" font="default" size="100%">George, Sameera S.</style></author><author><style face="normal" font="default" size="100%">Gerhard, Daniela S.</style></author><author><style face="normal" font="default" size="100%">Gerthoffert, Francois</style></author><author><style face="normal" font="default" size="100%">Gomez, Fauzi</style></author><author><style face="normal" font="default" size="100%">Han, Kang</style></author><author><style face="normal" font="default" size="100%">Hernandez, Kyle M.</style></author><author><style face="normal" font="default" size="100%">Issac, Biju</style></author><author><style face="normal" font="default" size="100%">Jackson, Richard</style></author><author><style face="normal" font="default" size="100%">Jensen, Mark A.</style></author><author><style face="normal" font="default" size="100%">Joshi, Sid</style></author><author><style face="normal" font="default" size="100%">Kadam, Ajinkya</style></author><author><style face="normal" font="default" size="100%">Khurana, Aishmit</style></author><author><style face="normal" font="default" size="100%">Kim, Kyle M. J.</style></author><author><style face="normal" font="default" size="100%">Kraft, Victoria E.</style></author><author><style face="normal" font="default" size="100%">Li, Shenglai</style></author><author><style face="normal" font="default" size="100%">Lichtenberg, Tara M.</style></author><author><style face="normal" font="default" size="100%">Lodato, Janice</style></author><author><style face="normal" font="default" size="100%">Lolla, Laxmi</style></author><author><style face="normal" font="default" size="100%">Martinov, Plamen</style></author><author><style face="normal" font="default" size="100%">Mazzone, Jeffrey A.</style></author><author><style face="normal" font="default" size="100%">Miller, Daniel P.</style></author><author><style face="normal" font="default" size="100%">Miller, Ian</style></author><author><style face="normal" font="default" size="100%">Miller, Joshua S.</style></author><author><style face="normal" font="default" size="100%">Miyauchi, Koji</style></author><author><style face="normal" font="default" size="100%">Murphy, Mark W.</style></author><author><style face="normal" font="default" size="100%">Nullet, Thomas</style></author><author><style face="normal" font="default" size="100%">Ogwara, Rowland O.</style></author><author><style face="normal" font="default" size="100%">Ortuño, Francisco M.</style></author><author><style face="normal" font="default" size="100%">Pedrosa, Jesús</style></author><author><style face="normal" font="default" size="100%">Pham, Phuong L.</style></author><author><style face="normal" font="default" size="100%">Popov, Maxim Y.</style></author><author><style face="normal" font="default" size="100%">Porter, James J.</style></author><author><style face="normal" font="default" size="100%">Powell, Raymond</style></author><author><style face="normal" font="default" size="100%">Rademacher, Karl</style></author><author><style face="normal" font="default" size="100%">Reid, Colin P.</style></author><author><style face="normal" font="default" size="100%">Rich, Samantha</style></author><author><style face="normal" font="default" size="100%">Rogel, Bessie</style></author><author><style face="normal" font="default" size="100%">Sahni, Himanso</style></author><author><style face="normal" font="default" size="100%">Savage, Jeremiah H.</style></author><author><style face="normal" font="default" size="100%">Schmitt, Kyle A.</style></author><author><style face="normal" font="default" size="100%">Simmons, Trevar J.</style></author><author><style face="normal" font="default" size="100%">Sislow, Joseph</style></author><author><style face="normal" font="default" size="100%">Spring, Jonathan</style></author><author><style face="normal" font="default" size="100%">Stein, Lincoln</style></author><author><style face="normal" font="default" size="100%">Sullivan, Sean</style></author><author><style face="normal" font="default" size="100%">Tang, Yajing</style></author><author><style face="normal" font="default" size="100%">Thiagarajan, Mathangi</style></author><author><style face="normal" font="default" size="100%">Troyer, Heather D.</style></author><author><style face="normal" font="default" size="100%">Wang, Chang</style></author><author><style face="normal" font="default" size="100%">Wang, Zhining</style></author><author><style face="normal" font="default" size="100%">West, Bedford L.</style></author><author><style face="normal" font="default" size="100%">Wilmer, Alex</style></author><author><style face="normal" font="default" size="100%">Wilson, Shane</style></author><author><style face="normal" font="default" size="100%">Wu, Kaman</style></author><author><style face="normal" font="default" size="100%">Wysocki, William P.</style></author><author><style face="normal" font="default" size="100%">Xiang, Linda</style></author><author><style face="normal" font="default" size="100%">Yamada, Joseph T.</style></author><author><style face="normal" font="default" size="100%">Yang, Liming</style></author><author><style face="normal" font="default" size="100%">Yu, Christine</style></author><author><style face="normal" font="default" size="100%">Yung, Christina K.</style></author><author><style face="normal" font="default" size="100%">Zenklusen, Jean Claude</style></author><author><style face="normal" font="default" size="100%">Zhang, Junjun</style></author><author><style face="normal" font="default" size="100%">Zhang, Zhenyu</style></author><author><style face="normal" font="default" size="100%">Zhao, Yuanheng</style></author><author><style face="normal" font="default" size="100%">Zubair, Ariz</style></author><author><style face="normal" font="default" size="100%">Staudt, Louis M.</style></author><author><style face="normal" font="default" size="100%">Grossman, Robert L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The NCI Genomic Data Commons</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Genetics</style></secondary-title><short-title><style face="normal" font="default" size="100%">Nat Genet</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct-02-2022</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/s41588-021-00791-5</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Muñoyerro-Muñiz, Dolores</style></author><author><style face="normal" font="default" size="100%">Villegas, Román</style></author><author><style face="normal" font="default" size="100%">López-Miranda, José</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Baño, Jesús</style></author><author><style face="normal" font="default" size="100%">Túnez, Isaac</style></author><author><style face="normal" font="default" size="100%">Bouillon, Roger</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Quesada Gomez, Jose Manuel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Real world evidence of calcifediol or vitamin D prescription and mortality rate of COVID-19 in a retrospective cohort of hospitalized Andalusian patients.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Calcifediol</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Kaplan-Meier Estimate</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Survival Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Vitamin D</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 12 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">23380</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;COVID-19 is a major worldwide health problem because of acute respiratory distress syndrome, and mortality. Several lines of evidence have suggested a relationship between the vitamin D endocrine system and severity of COVID-19. We present a survival study on a retrospective cohort of 15,968 patients, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Based on a central registry of electronic health records (the Andalusian Population Health Database, BPS), prescription of vitamin D or its metabolites within 15-30 days before hospitalization were recorded. The effect of prescription of vitamin D (metabolites) for other indication previous to the hospitalization was studied with respect to patient survival. Kaplan-Meier survival curves and hazard ratios support an association between prescription of these metabolites and patient survival. Such association was stronger for calcifediol (Hazard Ratio, HR = 0.67, with 95% confidence interval, CI, of [0.50-0.91]) than for cholecalciferol (HR = 0.75, with 95% CI of [0.61-0.91]), when prescribed 15 days prior hospitalization. Although the relation is maintained, there is a general decrease of this effect when a longer period of 30 days prior hospitalization is considered (calcifediol HR = 0.73, with 95% CI [0.57-0.95] and cholecalciferol HR = 0.88, with 95% CI [0.75, 1.03]), suggesting that association was stronger when the prescription was closer to the hospitalization.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mirzayi, Chloe</style></author><author><style face="normal" font="default" size="100%">Renson, Audrey</style></author><author><style face="normal" font="default" size="100%">Zohra, Fatima</style></author><author><style face="normal" font="default" size="100%">Elsafoury, Shaimaa</style></author><author><style face="normal" font="default" size="100%">Geistlinger, Ludwig</style></author><author><style face="normal" font="default" size="100%">Kasselman, Lora J</style></author><author><style face="normal" font="default" size="100%">Eckenrode, Kelly</style></author><author><style face="normal" font="default" size="100%">van de Wijgert, Janneke</style></author><author><style face="normal" font="default" size="100%">Loughman, Amy</style></author><author><style face="normal" font="default" size="100%">Marques, Francine Z</style></author><author><style face="normal" font="default" size="100%">MacIntyre, David A</style></author><author><style face="normal" font="default" size="100%">Arumugam, Manimozhiyan</style></author><author><style face="normal" font="default" size="100%">Azhar, Rimsha</style></author><author><style face="normal" font="default" size="100%">Beghini, Francesco</style></author><author><style face="normal" font="default" size="100%">Bergstrom, Kirk</style></author><author><style face="normal" font="default" size="100%">Bhatt, Ami</style></author><author><style face="normal" font="default" size="100%">Bisanz, Jordan E</style></author><author><style face="normal" font="default" size="100%">Braun, Jonathan</style></author><author><style face="normal" font="default" size="100%">Bravo, Hector Corrada</style></author><author><style face="normal" font="default" size="100%">Buck, Gregory A</style></author><author><style face="normal" font="default" size="100%">Bushman, Frederic</style></author><author><style face="normal" font="default" size="100%">Casero, David</style></author><author><style face="normal" font="default" size="100%">Clarke, Gerard</style></author><author><style face="normal" font="default" size="100%">Collado, Maria Carmen</style></author><author><style face="normal" font="default" size="100%">Cotter, Paul D</style></author><author><style face="normal" font="default" size="100%">Cryan, John F</style></author><author><style face="normal" font="default" size="100%">Demmer, Ryan T</style></author><author><style face="normal" font="default" size="100%">Devkota, Suzanne</style></author><author><style face="normal" font="default" size="100%">Elinav, Eran</style></author><author><style face="normal" font="default" size="100%">Escobar, Juan S</style></author><author><style face="normal" font="default" size="100%">Fettweis, Jennifer</style></author><author><style face="normal" font="default" size="100%">Finn, Robert D</style></author><author><style face="normal" font="default" size="100%">Fodor, Anthony A</style></author><author><style face="normal" font="default" size="100%">Forslund, Sofia</style></author><author><style face="normal" font="default" size="100%">Franke, Andre</style></author><author><style face="normal" font="default" size="100%">Furlanello, Cesare</style></author><author><style face="normal" font="default" size="100%">Gilbert, Jack</style></author><author><style face="normal" font="default" size="100%">Grice, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Haibe-Kains, Benjamin</style></author><author><style face="normal" font="default" size="100%">Handley, Scott</style></author><author><style face="normal" font="default" size="100%">Herd, Pamela</style></author><author><style face="normal" font="default" size="100%">Holmes, Susan</style></author><author><style face="normal" font="default" size="100%">Jacobs, Jonathan P</style></author><author><style face="normal" font="default" size="100%">Karstens, Lisa</style></author><author><style face="normal" font="default" size="100%">Knight, Rob</style></author><author><style face="normal" font="default" size="100%">Knights, Dan</style></author><author><style face="normal" font="default" size="100%">Koren, Omry</style></author><author><style face="normal" font="default" size="100%">Kwon, Douglas S</style></author><author><style face="normal" font="default" size="100%">Langille, Morgan</style></author><author><style face="normal" font="default" size="100%">Lindsay, Brianna</style></author><author><style face="normal" font="default" size="100%">McGovern, Dermot</style></author><author><style face="normal" font="default" size="100%">McHardy, Alice C</style></author><author><style face="normal" font="default" size="100%">McWeeney, Shannon</style></author><author><style face="normal" font="default" size="100%">Mueller, Noel T</style></author><author><style face="normal" font="default" size="100%">Nezi, Luigi</style></author><author><style face="normal" font="default" size="100%">Olm, Matthew</style></author><author><style face="normal" font="default" size="100%">Palm, Noah</style></author><author><style face="normal" font="default" size="100%">Pasolli, Edoardo</style></author><author><style face="normal" font="default" size="100%">Raes, Jeroen</style></author><author><style face="normal" font="default" size="100%">Redinbo, Matthew R</style></author><author><style face="normal" font="default" size="100%">Rühlemann, Malte</style></author><author><style face="normal" font="default" size="100%">Balfour Sartor, R</style></author><author><style face="normal" font="default" size="100%">Schloss, Patrick D</style></author><author><style face="normal" font="default" size="100%">Schriml, Lynn</style></author><author><style face="normal" font="default" size="100%">Segal, Eran</style></author><author><style face="normal" font="default" size="100%">Shardell, Michelle</style></author><author><style face="normal" font="default" size="100%">Sharpton, Thomas</style></author><author><style face="normal" font="default" size="100%">Smirnova, Ekaterina</style></author><author><style face="normal" font="default" size="100%">Sokol, Harry</style></author><author><style face="normal" font="default" size="100%">Sonnenburg, Justin L</style></author><author><style face="normal" font="default" size="100%">Srinivasan, Sujatha</style></author><author><style face="normal" font="default" size="100%">Thingholm, Louise B</style></author><author><style face="normal" font="default" size="100%">Turnbaugh, Peter J</style></author><author><style face="normal" font="default" size="100%">Upadhyay, Vaibhav</style></author><author><style face="normal" font="default" size="100%">Walls, Ramona L</style></author><author><style face="normal" font="default" size="100%">Wilmes, Paul</style></author><author><style face="normal" font="default" size="100%">Yamada, Takuji</style></author><author><style face="normal" font="default" size="100%">Zeller, Georg</style></author><author><style face="normal" font="default" size="100%">Zhang, Mingyu</style></author><author><style face="normal" font="default" size="100%">Zhao, Ni</style></author><author><style face="normal" font="default" size="100%">Zhao, Liping</style></author><author><style face="normal" font="default" size="100%">Bao, Wenjun</style></author><author><style face="normal" font="default" size="100%">Culhane, Aedin</style></author><author><style face="normal" font="default" size="100%">Devanarayan, Viswanath</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Fan, Xiaohui</style></author><author><style face="normal" font="default" size="100%">Fischer, Matthias</style></author><author><style face="normal" font="default" size="100%">Jones, Wendell</style></author><author><style face="normal" font="default" size="100%">Kusko, Rebecca</style></author><author><style face="normal" font="default" size="100%">Mason, Christopher E</style></author><author><style face="normal" font="default" size="100%">Mercer, Tim R</style></author><author><style face="normal" font="default" size="100%">Sansone, Susanna-Assunta</style></author><author><style face="normal" font="default" size="100%">Scherer, Andreas</style></author><author><style face="normal" font="default" size="100%">Shi, Leming</style></author><author><style face="normal" font="default" size="100%">Thakkar, Shraddha</style></author><author><style face="normal" font="default" size="100%">Tong, Weida</style></author><author><style face="normal" font="default" size="100%">Wolfinger, Russ</style></author><author><style face="normal" font="default" size="100%">Hunter, Christopher</style></author><author><style face="normal" font="default" size="100%">Segata, Nicola</style></author><author><style face="normal" font="default" size="100%">Huttenhower, Curtis</style></author><author><style face="normal" font="default" size="100%">Dowd, Jennifer B</style></author><author><style face="normal" font="default" size="100%">Jones, Heidi E</style></author><author><style face="normal" font="default" size="100%">Waldron, Levi</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Genomic Standards Consortium</style></author><author><style face="normal" font="default" size="100%">Massive Analysis and Quality Control Society</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Reporting guidelines for human microbiome research: the STORMS checklist.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Dysbiosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbiota</style></keyword><keyword><style  face="normal" font="default" size="100%">Observational Studies as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Research Design</style></keyword><keyword><style  face="normal" font="default" size="100%">Translational Science, Biomedical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">1885-1892</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/34789871?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tenorio-Castaño, Jair</style></author><author><style face="normal" font="default" size="100%">Morte, Beatriz</style></author><author><style face="normal" font="default" size="100%">Nevado, Julián</style></author><author><style face="normal" font="default" size="100%">Martínez-Glez, Víctor</style></author><author><style face="normal" font="default" size="100%">Santos-Simarro, Fernando</style></author><author><style face="normal" font="default" size="100%">García-Miñaur, Sixto</style></author><author><style face="normal" font="default" size="100%">Palomares-Bralo, María</style></author><author><style face="normal" font="default" size="100%">Pacio-Míguez, Marta</style></author><author><style face="normal" font="default" size="100%">Gómez, Beatriz</style></author><author><style face="normal" font="default" size="100%">Arias, Pedro</style></author><author><style face="normal" font="default" size="100%">Alcochea, Alba</style></author><author><style face="normal" font="default" size="100%">Carrión, Juan</style></author><author><style face="normal" font="default" size="100%">Arias, Patricia</style></author><author><style face="normal" font="default" size="100%">Almoguera, Berta</style></author><author><style face="normal" font="default" size="100%">López-Grondona, Fermina</style></author><author><style face="normal" font="default" size="100%">Lorda-Sanchez, Isabel</style></author><author><style face="normal" font="default" size="100%">Galán-Gómez, Enrique</style></author><author><style face="normal" font="default" size="100%">Valenzuela, Irene</style></author><author><style face="normal" font="default" size="100%">Méndez Perez, María</style></author><author><style face="normal" font="default" size="100%">Cuscó, Ivón</style></author><author><style face="normal" font="default" size="100%">Barros, Francisco</style></author><author><style face="normal" font="default" size="100%">Pié, Juan</style></author><author><style face="normal" font="default" size="100%">Ramos, Sergio</style></author><author><style face="normal" font="default" size="100%">Ramos, Feliciano</style></author><author><style face="normal" font="default" size="100%">Kuechler, Alma</style></author><author><style face="normal" font="default" size="100%">Tizzano, Eduardo</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author><author><style face="normal" font="default" size="100%">Kaiser, Frank</style></author><author><style face="normal" font="default" size="100%">Pérez-Jurado, Luis</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Lapunzina, Pablo</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">The ENoD-CIBERER Consortium</style></author><author><style face="normal" font="default" size="100%">The SIDE Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Schuurs–Hoeijmakers Syndrome (PACS1 Neurodevelopmental Disorder): Seven Novel Patients and a Review</style></title><secondary-title><style face="normal" font="default" size="100%">Genes</style></secondary-title><short-title><style face="normal" font="default" size="100%">Genes</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-05-2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2073-4425/12/5/738https://www.mdpi.com/2073-4425/12/5/738/pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">738</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Díez-Fuertes, F</style></author><author><style face="normal" font="default" size="100%">De La Torre-Tarazona, H E</style></author><author><style face="normal" font="default" size="100%">Calonge, E</style></author><author><style face="normal" font="default" size="100%">Pernas, M</style></author><author><style face="normal" font="default" size="100%">Bermejo, M</style></author><author><style face="normal" font="default" size="100%">García-Pérez, J</style></author><author><style face="normal" font="default" size="100%">Álvarez, A</style></author><author><style face="normal" font="default" size="100%">Capa, L</style></author><author><style face="normal" font="default" size="100%">García-García, F</style></author><author><style face="normal" font="default" size="100%">Saumoy, M</style></author><author><style face="normal" font="default" size="100%">Riera, M</style></author><author><style face="normal" font="default" size="100%">Boland-Auge, A</style></author><author><style face="normal" font="default" size="100%">López-Galíndez, C</style></author><author><style face="normal" font="default" size="100%">Lathrop, M</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Sakuntabhai, A</style></author><author><style face="normal" font="default" size="100%">Alcamí, J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association of a single nucleotide polymorphism in the ubxn6 gene with long-term non-progression phenotype in HIV-positive individuals.</style></title><secondary-title><style face="normal" font="default" size="100%">Clin Microbiol Infect</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Clin Microbiol Infect</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptor Proteins, Vesicular Transport</style></keyword><keyword><style  face="normal" font="default" size="100%">Autophagy-Related Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Caveolin 1</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Dendritic Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease Progression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockdown Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">HeLa Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV Long-Term Survivors</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV-1</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Macrophages</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">whole exome sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">107-114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;The long-term non-progressors (LTNPs) are a heterogeneous group of HIV-positive individuals characterized by their ability to maintain high CD4 T-cell counts and partially control viral replication for years in the absence of antiretroviral therapy. The present study aims to identify host single nucleotide polymorphisms (SNPs) associated with non-progression in a cohort of 352 individuals.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;DNA microarrays and exome sequencing were used for genotyping about 240 000 functional polymorphisms throughout more than 20 000 human genes. The allele frequencies of 85 LTNPs were compared with a control population. SNPs associated with LTNPs were confirmed in a population of typical progressors. Functional analyses in the affected gene were carried out through knockdown experiments in HeLa-P4, macrophages and dendritic cells.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Several SNPs located within the major histocompatibility complex region previously related to LTNPs were confirmed in this new cohort. The SNP rs1127888 (UBXN6) surpassed the statistical significance of these markers after Bonferroni correction (q = 2.11 × 10). An uncommon allelic frequency of rs1127888 among LTNPs was confirmed by comparison with typical progressors and other publicly available populations. UBXN6 knockdown experiments caused an increase in CAV1 expression and its accumulation in the plasma membrane. In vitro infection of different cell types with HIV-1 replication-competent recombinant viruses caused a reduction of the viral replication capacity compared with their corresponding wild-type cells expressing UBXN6.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;A higher prevalence of Ala31Thr in UBXN6 was found among LTNPs within its N-terminal region, which is crucial for UBXN6/VCP protein complex formation. UBXN6 knockdown affected CAV1 turnover and HIV-1 replication capacity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31158522?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yang, Mi</style></author><author><style face="normal" font="default" size="100%">Petralia, Francesca</style></author><author><style face="normal" font="default" size="100%">Li, Zhi</style></author><author><style face="normal" font="default" size="100%">Li, Hongyang</style></author><author><style face="normal" font="default" size="100%">Ma, Weiping</style></author><author><style face="normal" font="default" size="100%">Song, Xiaoyu</style></author><author><style face="normal" font="default" size="100%">Kim, Sunkyu</style></author><author><style face="normal" font="default" size="100%">Lee, Heewon</style></author><author><style face="normal" font="default" size="100%">Yu, Han</style></author><author><style face="normal" font="default" size="100%">Lee, Bora</style></author><author><style face="normal" font="default" size="100%">Bae, Seohui</style></author><author><style face="normal" font="default" size="100%">Heo, Eunji</style></author><author><style face="normal" font="default" size="100%">Kaczmarczyk, Jan</style></author><author><style face="normal" font="default" size="100%">Stępniak, Piotr</style></author><author><style face="normal" font="default" size="100%">Warchoł, Michał</style></author><author><style face="normal" font="default" size="100%">Yu, Thomas</style></author><author><style face="normal" font="default" size="100%">Calinawan, Anna P</style></author><author><style face="normal" font="default" size="100%">Boutros, Paul C</style></author><author><style face="normal" font="default" size="100%">Payne, Samuel H</style></author><author><style face="normal" font="default" size="100%">Reva, Boris</style></author><author><style face="normal" font="default" size="100%">Boja, Emily</style></author><author><style face="normal" font="default" size="100%">Rodriguez, Henry</style></author><author><style face="normal" font="default" size="100%">Stolovitzky, Gustavo</style></author><author><style face="normal" font="default" size="100%">Guan, Yuanfang</style></author><author><style face="normal" font="default" size="100%">Kang, Jaewoo</style></author><author><style face="normal" font="default" size="100%">Wang, Pei</style></author><author><style face="normal" font="default" size="100%">Fenyö, David</style></author><author><style face="normal" font="default" size="100%">Saez-Rodriguez, Julio</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NCI-CPTAC-DREAM Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Syst</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell Syst</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Crowdsourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Machine Learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphoproteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 08 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">186-195.e9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cancer is driven by genomic alterations, but the processes causing this disease are largely performed by proteins. However, proteins are harder and more expensive to measure than genes and transcripts. To catalyze developments of methods to infer protein levels from other omics measurements, we leveraged crowdsourcing via the NCI-CPTAC DREAM proteogenomic challenge. We asked for methods to predict protein and phosphorylation levels from genomic and transcriptomic data in cancer patients. The best performance was achieved by an ensemble of models, including as predictors transcript level of the corresponding genes, interaction between genes, conservation across tumor types, and phosphosite proximity for phosphorylation prediction. Proteins from metabolic pathways and complexes were the best and worst predicted, respectively. The performance of even the best-performing model was modest, suggesting that many proteins are strongly regulated through translational control and degradation. Our results set a reference for the limitations of computational inference in proteogenomics. A record of this paper's transparent peer review process is included in the Supplemental Information.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32710834?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Falco, Matias M</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection.</style></title><secondary-title><style face="normal" font="default" size="100%">Signal Transduct Target Ther</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Signal Transduct Target Ther</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">drug repositioning</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Machine Learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Docking Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Targeted Therapy</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 12 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">290</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33311438?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Salgado, David</style></author><author><style face="normal" font="default" size="100%">Armean, Irina M</style></author><author><style face="normal" font="default" size="100%">Baudis, Michael</style></author><author><style face="normal" font="default" size="100%">Beltran, Sergi</style></author><author><style face="normal" font="default" size="100%">Capella-Gutíerrez, Salvador</style></author><author><style face="normal" font="default" size="100%">Carvalho-Silva, Denise</style></author><author><style face="normal" font="default" size="100%">Dominguez Del Angel, Victoria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Furlong, Laura I</style></author><author><style face="normal" font="default" size="100%">Gao, Bo</style></author><author><style face="normal" font="default" size="100%">Garcia, Leyla</style></author><author><style face="normal" font="default" size="100%">Gerloff, Dietlind</style></author><author><style face="normal" font="default" size="100%">Gut, Ivo</style></author><author><style face="normal" font="default" size="100%">Gyenesei, Attila</style></author><author><style face="normal" font="default" size="100%">Habermann, Nina</style></author><author><style face="normal" font="default" size="100%">Hancock, John M</style></author><author><style face="normal" font="default" size="100%">Hanauer, Marc</style></author><author><style face="normal" font="default" size="100%">Hovig, Eivind</style></author><author><style face="normal" font="default" size="100%">Johansson, Lennart F</style></author><author><style face="normal" font="default" size="100%">Keane, Thomas</style></author><author><style face="normal" font="default" size="100%">Korbel, Jan</style></author><author><style face="normal" font="default" size="100%">Lauer, Katharina B</style></author><author><style face="normal" font="default" size="100%">Laurie, Steve</style></author><author><style face="normal" font="default" size="100%">Leskošek, Brane</style></author><author><style face="normal" font="default" size="100%">Lloyd, David</style></author><author><style face="normal" font="default" size="100%">Marqués-Bonet, Tomás</style></author><author><style face="normal" font="default" size="100%">Mei, Hailiang</style></author><author><style face="normal" font="default" size="100%">Monostory, Katalin</style></author><author><style face="normal" font="default" size="100%">Piñero, Janet</style></author><author><style face="normal" font="default" size="100%">Poterlowicz, Krzysztof</style></author><author><style face="normal" font="default" size="100%">Rath, Ana</style></author><author><style face="normal" font="default" size="100%">Samarakoon, Pubudu</style></author><author><style face="normal" font="default" size="100%">Sanz, Ferran</style></author><author><style face="normal" font="default" size="100%">Saunders, Gary</style></author><author><style face="normal" font="default" size="100%">Sie, Daoud</style></author><author><style face="normal" font="default" size="100%">Swertz, Morris A</style></author><author><style face="normal" font="default" size="100%">Tsukanov, Kirill</style></author><author><style face="normal" font="default" size="100%">Valencia, Alfonso</style></author><author><style face="normal" font="default" size="100%">Vidak, Marko</style></author><author><style face="normal" font="default" size="100%">Yenyxe González, Cristina</style></author><author><style face="normal" font="default" size="100%">Ylstra, Bauke</style></author><author><style face="normal" font="default" size="100%">Béroud, Christophe</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research.</style></title><secondary-title><style face="normal" font="default" size="100%">F1000Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">F1000Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While &quot;High-Throughput&quot; sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established   with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/34367618?dopt=Abstract</style></custom1><section><style face="normal" font="default" size="100%">1229</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Palomero, Luis</style></author><author><style face="normal" font="default" size="100%">Galván-Femenía, Ivan</style></author><author><style face="normal" font="default" size="100%">de Cid, Rafael</style></author><author><style face="normal" font="default" size="100%">Espín, Roderic</style></author><author><style face="normal" font="default" size="100%">Barnes, Daniel R</style></author><author><style face="normal" font="default" size="100%">Blommaert, Eline</style></author><author><style face="normal" font="default" size="100%">Gil-Gil, Miguel</style></author><author><style face="normal" font="default" size="100%">Falo, Catalina</style></author><author><style face="normal" font="default" size="100%">Stradella, Agostina</style></author><author><style face="normal" font="default" size="100%">Ouchi, Dan</style></author><author><style face="normal" font="default" size="100%">Roso-Llorach, Albert</style></author><author><style face="normal" font="default" size="100%">Violan, Concepció</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Extremera, Ana Isabel</style></author><author><style face="normal" font="default" size="100%">García-Valero, Mar</style></author><author><style face="normal" font="default" size="100%">Herranz, Carmen</style></author><author><style face="normal" font="default" size="100%">Mateo, Francesca</style></author><author><style face="normal" font="default" size="100%">Mereu, Elisabetta</style></author><author><style face="normal" font="default" size="100%">Beesley, Jonathan</style></author><author><style face="normal" font="default" size="100%">Chenevix-Trench, Georgia</style></author><author><style face="normal" font="default" size="100%">Roux, Cecilia</style></author><author><style face="normal" font="default" size="100%">Mak, Tak</style></author><author><style face="normal" font="default" size="100%">Brunet, Joan</style></author><author><style face="normal" font="default" size="100%">Hakem, Razq</style></author><author><style face="normal" font="default" size="100%">Gorrini, Chiara</style></author><author><style face="normal" font="default" size="100%">Antoniou, Antonis C</style></author><author><style face="normal" font="default" size="100%">Lázaro, Conxi</style></author><author><style face="normal" font="default" size="100%">Pujana, Miquel Angel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Immune Cell Associations with Cancer Risk.</style></title><secondary-title><style face="normal" font="default" size="100%">iScience</style></secondary-title><alt-title><style face="normal" font="default" size="100%">iScience</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Jul 24</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">101296</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32622267?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Grignani, Giovanni</style></author><author><style face="normal" font="default" size="100%">Martinez-Trufero, Javier</style></author><author><style face="normal" font="default" size="100%">Redondo, Andres</style></author><author><style face="normal" font="default" size="100%">Valverde, Claudia</style></author><author><style face="normal" font="default" size="100%">Stacchiotti, Silvia</style></author><author><style face="normal" font="default" size="100%">Lopez-Pousa, Antonio</style></author><author><style face="normal" font="default" size="100%">D'Ambrosio, Lorenzo</style></author><author><style face="normal" font="default" size="100%">Gutierrez, Antonio</style></author><author><style face="normal" font="default" size="100%">Perez-Vega, Herminia</style></author><author><style face="normal" font="default" size="100%">Encinas-Tobajas, Victor</style></author><author><style face="normal" font="default" size="100%">de Alava, Enrique</style></author><author><style face="normal" font="default" size="100%">Collini, Paola</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Carrasco-Garcia, Irene</style></author><author><style face="normal" font="default" size="100%">Lopez-Alvarez, Maria</style></author><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">Lopez-Martin, Jose A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Nivolumab and sunitinib combination in advanced soft tissue sarcomas: a multicenter, single-arm, phase Ib/II trial.</style></title><secondary-title><style face="normal" font="default" size="100%">J Immunother Cancer</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Immunother Cancer</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Antineoplastic Agents, Immunological</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Nivolumab</style></keyword><keyword><style  face="normal" font="default" size="100%">Sarcoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Sunitinib</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Sarcomas exhibit low expression of factors related to immune response, which could explain the modest activity of PD-1 inhibitors. A potential strategy to convert a cold into an inflamed microenvironment lies on a combination therapy. As tumor angiogenesis promotes immunosuppression, we designed a phase Ib/II trial to test the double inhibition of angiogenesis (sunitinib) and PD-1/PD-L1 axis (nivolumab).&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;This single-arm, phase Ib/II trial enrolled adult patients with selected subtypes of sarcoma. Phase Ib established two dose levels: level 0 with sunitinib 37.5 mg daily from day 1, plus nivolumab 3 mg/kg intravenously on day 15, and then every 2 weeks; and level -1 with sunitinib 37.5 mg on the first 14 days (induction) and then 25 mg per day plus nivolumab on the same schedule. The primary endpoint was to determine the recommended dose for phase II (phase I) and the 6-month progression-free survival rate, according to Response Evaluation Criteria in Solid Tumors 1.1 (phase II).&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;From May 2017 to April 2019, 68 patients were enrolled: 16 in phase Ib and 52 in phase II. The recommended dose of sunitinib for phase II was 37.5 mg as induction and then 25 mg in combination with nivolumab. After a median follow-up of 17 months (4-26), the 6-month progression-free survival rate was 48% (95% CI 41% to 55%). The most common grade 3-4 adverse events included transaminitis (17.3%) and neutropenia (11.5%).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Sunitinib plus nivolumab is an active scheme with manageable toxicity in the treatment of selected patients with advanced soft tissue sarcoma, with almost half of patients free of progression at 6 months. NCT03277924.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33203665?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bogliolo, Massimo</style></author><author><style face="normal" font="default" size="100%">Pujol, Roser</style></author><author><style face="normal" font="default" size="100%">Aza-Carmona, Miriam</style></author><author><style face="normal" font="default" size="100%">Muñoz-Subirana, Núria</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santiago, Benjamin</style></author><author><style face="normal" font="default" size="100%">Casado, José Antonio</style></author><author><style face="normal" font="default" size="100%">Rio, Paula</style></author><author><style face="normal" font="default" size="100%">Bauser, Christopher</style></author><author><style face="normal" font="default" size="100%">Reina-Castillón, Judith</style></author><author><style face="normal" font="default" size="100%">Lopez-Sanchez, Marcos</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Quereda, Lidia</style></author><author><style face="normal" font="default" size="100%">Gallano, Pia</style></author><author><style face="normal" font="default" size="100%">Catalá, Albert</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llobet, Ana</style></author><author><style face="normal" font="default" size="100%">Badell, Isabel</style></author><author><style face="normal" font="default" size="100%">Diaz-Heredia, Cristina</style></author><author><style face="normal" font="default" size="100%">Hladun, Raquel</style></author><author><style face="normal" font="default" size="100%">Senent, Leonort</style></author><author><style face="normal" font="default" size="100%">Argiles, Bienvenida</style></author><author><style face="normal" font="default" size="100%">Bergua Burgues, Juan Miguel</style></author><author><style face="normal" font="default" size="100%">Bañez, Fatima</style></author><author><style face="normal" font="default" size="100%">Arrizabalaga, Beatriz</style></author><author><style face="normal" font="default" size="100%">López Almaraz, Ricardo</style></author><author><style face="normal" font="default" size="100%">Lopez, Monica</style></author><author><style face="normal" font="default" size="100%">Figuera, Ángela</style></author><author><style face="normal" font="default" size="100%">Molinés, Antonio</style></author><author><style face="normal" font="default" size="100%">Pérez de Soto, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Hernando, Inés</style></author><author><style face="normal" font="default" size="100%">Muñoz, Juan Antonio</style></author><author><style face="normal" font="default" size="100%">Del Rosario Marin, Maria</style></author><author><style face="normal" font="default" size="100%">Balmaña, Judith</style></author><author><style face="normal" font="default" size="100%">Stjepanovic, Neda</style></author><author><style face="normal" font="default" size="100%">Carrasco, Estela</style></author><author><style face="normal" font="default" size="100%">Cuesta, Isabel</style></author><author><style face="normal" font="default" size="100%">Cosuelo, José Miguel</style></author><author><style face="normal" font="default" size="100%">Regueiro, Alexandra</style></author><author><style face="normal" font="default" size="100%">Moraleda Jimenez, José</style></author><author><style face="normal" font="default" size="100%">Galera-Miñarro, Ana Maria</style></author><author><style face="normal" font="default" size="100%">Rosiñol, Laura</style></author><author><style face="normal" font="default" size="100%">Carrió, Anna</style></author><author><style face="normal" font="default" size="100%">Beléndez-Bieler, Cristina</style></author><author><style face="normal" font="default" size="100%">Escudero Soto, Antonio</style></author><author><style face="normal" font="default" size="100%">Cela, Elena</style></author><author><style face="normal" font="default" size="100%">de la Mata, Gregorio</style></author><author><style face="normal" font="default" size="100%">Fernández-Delgado, Rafael</style></author><author><style face="normal" font="default" size="100%">Garcia-Pardos, Maria Carmen</style></author><author><style face="normal" font="default" size="100%">Sáez-Villaverde, Raquel</style></author><author><style face="normal" font="default" size="100%">Barragaño, Marta</style></author><author><style face="normal" font="default" size="100%">Portugal, Raquel</style></author><author><style face="normal" font="default" size="100%">Lendinez, Francisco</style></author><author><style face="normal" font="default" size="100%">Hernadez, Ines</style></author><author><style face="normal" font="default" size="100%">Vagace, José Manue</style></author><author><style face="normal" font="default" size="100%">Tapia, Maria</style></author><author><style face="normal" font="default" size="100%">Nieto, José</style></author><author><style face="normal" font="default" size="100%">Garcia, Marta</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Macarena</style></author><author><style face="normal" font="default" size="100%">Vicho, Cristina</style></author><author><style face="normal" font="default" size="100%">Galvez, Eva</style></author><author><style face="normal" font="default" size="100%">Valiente, Alberto</style></author><author><style face="normal" font="default" size="100%">Antelo, Maria Luisa</style></author><author><style face="normal" font="default" size="100%">Ancliff, Phil</style></author><author><style face="normal" font="default" size="100%">García, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Sevilla, Julian</style></author><author><style face="normal" font="default" size="100%">Paprotka, Tobias</style></author><author><style face="normal" font="default" size="100%">Pérez-Jurado, Luis Alberto</style></author><author><style face="normal" font="default" size="100%">Bueren, Juan</style></author><author><style face="normal" font="default" size="100%">Surralles, Jordi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies.</style></title><secondary-title><style face="normal" font="default" size="100%">J Med Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Med Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cell Line</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Repair</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Fanconi Anemia Complementation Group A Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockout Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">whole exome sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">258-268</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;PURPOSE: &lt;/b&gt;Patients with Fanconi anaemia (FA), a rare DNA repair genetic disease, exhibit chromosome fragility, bone marrow failure, malformations and cancer susceptibility. FA molecular diagnosis is challenging since FA is caused by point mutations and large deletions in 22 genes following three heritability patterns. To optimise FA patients' characterisation, we developed a simplified but effective methodology based on whole exome sequencing (WES) and functional studies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;68 patients with FA were analysed by commercial WES services. Copy number variations were evaluated by sequencing data analysis with RStudio. To test  missense variants, wt FANCA cDNA was cloned and variants were introduced by site-directed mutagenesis. Vectors were then tested for their ability to complement DNA repair defects of a FANCA-KO human cell line generated by TALEN technologies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We identified 93.3% of mutated alleles including large deletions. We determined the pathogenicity of three FANCA missense variants and demonstrated that two  variants reported in mutations databases as 'affecting functions' are SNPs. Deep analysis of sequencing data revealed patients' true mutations, highlighting the importance of functional analysis. In one patient, no pathogenic variant could be identified in any of the 22 known FA genes, and in seven patients, only one deleterious variant could be identified (three patients each with FANCA and FANCD2 and one patient with FANCE mutations) CONCLUSION: WES and proper bioinformatics analysis are sufficient to effectively characterise patients with FA regardless of the rarity of their complementation group, type of mutations, mosaic condition and DNA source.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31586946?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author><author><style face="normal" font="default" size="100%">Cruz, Josefina</style></author><author><style face="normal" font="default" size="100%">Penel, Nicolas</style></author><author><style face="normal" font="default" size="100%">Le Cesne, Axel</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Luna, Pablo</style></author><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">Bernabeu, Daniel</style></author><author><style face="normal" font="default" size="100%">de Alava, Enrique</style></author><author><style face="normal" font="default" size="100%">Lopez-Guerrero, Jose Antonio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Gutierrez, Antonio</style></author><author><style face="normal" font="default" size="100%">Collini, Paola</style></author><author><style face="normal" font="default" size="100%">Karanian, Marie</style></author><author><style face="normal" font="default" size="100%">Redondo, Andres</style></author><author><style face="normal" font="default" size="100%">Lopez-Pousa, Antonio</style></author><author><style face="normal" font="default" size="100%">Grignani, Giovanni</style></author><author><style face="normal" font="default" size="100%">Diaz-Martin, Juan</style></author><author><style face="normal" font="default" size="100%">Marcilla, David</style></author><author><style face="normal" font="default" size="100%">Fernandez-Serra, Antonio</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Aguilera, Cristina</style></author><author><style face="normal" font="default" size="100%">Casali, Paolo G</style></author><author><style face="normal" font="default" size="100%">Blay, Jean-Yves</style></author><author><style face="normal" font="default" size="100%">Stacchiotti, Silvia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pazopanib for treatment of typical solitary fibrous tumours: a multicentre, single-arm, phase 2 trial.</style></title><secondary-title><style face="normal" font="default" size="100%">Lancet Oncol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Lancet Oncol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Follow-Up Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Indazoles</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Metastasis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Kinase Inhibitors</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrimidines</style></keyword><keyword><style  face="normal" font="default" size="100%">Response Evaluation Criteria in Solid Tumors</style></keyword><keyword><style  face="normal" font="default" size="100%">Solitary Fibrous Tumors</style></keyword><keyword><style  face="normal" font="default" size="100%">Sulfonamides</style></keyword><keyword><style  face="normal" font="default" size="100%">Survival Rate</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">456-466</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Solitary fibrous tumour is an ultra-rare sarcoma, which encompasses different clinicopathological subgroups. The dedifferentiated subgroup shows an aggressive course with resistance to pazopanib, whereas in the malignant subgroup, pazopanib shows higher activity than in previous studies with chemotherapy. We designed a trial to test pazopanib activity in two different cohorts of solitary fibrous tumour: the malignant-dedifferentiated cohort, which was previously published, and the typical cohort, which is presented here.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;In this single-arm, phase 2 trial, adult patients (aged ≥18 years) diagnosed with confirmed metastatic or unresectable typical solitary fibrous tumour of any location, who had progressed in the previous 6 months (by Choi criteria or Response Evaluation Criteria in Solid Tumors [RECIST]) and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2 were enrolled at 11 tertiary hospitals in Italy, France, and Spain. Patients received pazopanib 800 mg once daily, taken orally, until progression, unacceptable toxicity, withdrawal of consent, non-compliance, or a delay in pazopanib administration of longer than 3 weeks. The primary endpoint was proportion of patients achieving an overall response measured by Choi criteria in patients who received at least 1 month of treatment with at least one radiological assessment. All patients who received at least one dose of the study drug were included in the safety analyses. This study is registered in ClinicalTrials.gov, NCT02066285, and with the European Clinical Trials Database, EudraCT 2013-005456-15.&lt;/p&gt;&lt;p&gt;&lt;b&gt;FINDINGS: &lt;/b&gt;From June 26, 2014, to Dec 13, 2018, of 40 patients who were assessed, 34 patients were enrolled and 31 patients were included in the response analysis. Median follow-up was 18 months (IQR 14-34), and 18 (58%) of 31 patients had a partial response, 12 (39%) had stable disease, and one (3%) showed progressive disease according to Choi criteria and central review. The proportion of overall response based on Choi criteria was 58% (95% CI 34-69). There were no deaths caused by toxicity, and the most frequent adverse events were diarrhoea (18 [53%] of 34 patients), fatigue (17 [50%]), and hypertension (17 [50%]).&lt;/p&gt;&lt;p&gt;&lt;b&gt;INTERPRETATION: &lt;/b&gt;To our knowledge, this is the first prospective trial of pazopanib for advanced typical solitary fibrous tumour. The manageable toxicity and activity shown by pazopanib in this cohort suggest that this drug could be considered as first-line treatment for advanced typical solitary fibrous tumour.&lt;/p&gt;&lt;p&gt;&lt;b&gt;FUNDING: &lt;/b&gt;Spanish Group for Research on Sarcomas (GEIS), Italian Sarcoma Group (ISG), French Sarcoma Group (FSG), GlaxoSmithKline, and Novartis.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32066540?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Galvez, Juan M</style></author><author><style face="normal" font="default" size="100%">Castillo-Secilla, Daniel</style></author><author><style face="normal" font="default" size="100%">Herrera, Luis J</style></author><author><style face="normal" font="default" size="100%">Valenzuela, Olga</style></author><author><style face="normal" font="default" size="100%">Caba, Octavio</style></author><author><style face="normal" font="default" size="100%">Prados, Jose C</style></author><author><style face="normal" font="default" size="100%">Ortuno, Francisco M</style></author><author><style face="normal" font="default" size="100%">Rojas, Ignacio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Towards Improving Skin Cancer Diagnosis by Integrating Microarray and RNA-Seq Datasets.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE J Biomed Health Inform</style></secondary-title><alt-title><style face="normal" font="default" size="100%">IEEE J Biomed Health Inform</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biomarkers, Tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Diagnosis, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Machine Learning</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-seq</style></keyword><keyword><style  face="normal" font="default" size="100%">Skin Neoplasms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">2119-2130</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Many clinical studies have revealed the high biological similarities existing among different skin pathological states. These similarities create difficulties in the efficient diagnosis of skin cancer, and encourage to study and design new intelligent clinical decision support systems. In this sense, gene expression analysis can help find differentially expressed genes (DEGs) simultaneously discerning multiple skin pathological states in a single test. The integration of multiple heterogeneous transcriptomic datasets requires different pipeline stages to be properly designed: from suitable batch merging and efficient biomarker selection to automated classification assessment. This article presents a novel approach addressing all these technical issues, with the intention of providing new sights about skin cancer diagnosis. Although new future efforts will have to be made in the search for better biomarkers recognizing specific skin pathological states, our study found a panel of 8 highly relevant multiclass DEGs for discerning up to 10 skin pathological states: 2 healthy skin conditions a priori, 2 cataloged precancerous skin diseases and 6 cancerous skin states. Their power of diagnosis over new samples was widely tested by previously well-trained classification models. Robust performance metrics such as overall and mean multiclass F1-score outperformed recognition rates of 94% and 80%, respectively. Clinicians should give special attention to highlighted multiclass DEGs that have high gene expression changes present among them, and understand their biological relationship to different skin pathological states.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31871000?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Casimiro-Soriguer, C S</style></author><author><style face="normal" font="default" size="100%">Rigual, M M</style></author><author><style face="normal" font="default" size="100%">Brokate-Llanos, A M</style></author><author><style face="normal" font="default" size="100%">Muñoz, M J</style></author><author><style face="normal" font="default" size="100%">Garzón, A</style></author><author><style face="normal" font="default" size="100%">Pérez-Pulido, A J</style></author><author><style face="normal" font="default" size="100%">Jimenez, J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using AnABlast for intergenic sORF prediction in the Caenorhabditis elegans genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Caenorhabditis elegans</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Open Reading Frames</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 12 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">4827-4832</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;MOTIVATION: &lt;/b&gt;Short bioactive peptides encoded by small open reading frames (sORFs) play important roles in eukaryotes. Bioinformatics prediction of ORFs is an early step in a genome sequence analysis, but sORFs encoding short peptides, often using non-AUG initiation codons, are not easily discriminated from false ORFs occurring by chance.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;AnABlast is a computational tool designed to highlight putative protein-coding regions in genomic DNA sequences. This protein-coding finder is independent of ORF length and reading frame shifts, thus making of AnABlast a potentially useful tool to predict sORFs. Using this algorithm, here, we report the identification of 82 putative new intergenic sORFs in the Caenorhabditis elegans genome. Sequence similarity, motif presence, expression data and RNA interference experiments support that the underlined sORFs likely encode functional peptides, encouraging the use of AnABlast as a new approach for the accurate prediction of intergenic sORFs in annotated eukaryotic genomes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;AVAILABILITY AND IMPLEMENTATION: &lt;/b&gt;AnABlast is freely available at http://www.bioinfocabd.upo.es/ab/. The C.elegans genome browser with AnABlast results, annotated genes and all data used in this study is available at http://www.bioinfocabd.upo.es/celegans.&lt;/p&gt;&lt;p&gt;&lt;b&gt;SUPPLEMENTARY INFORMATION: &lt;/b&gt;Supplementary data are available at Bioinformatics online.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">19</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32614398?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Salavert, Francisco</style></author><author><style face="normal" font="default" size="100%">Pujana, Miguel A</style></author><author><style face="normal" font="default" size="100%">Mateo, Francesca</style></author><author><style face="normal" font="default" size="100%">Herranz, Carmen</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models.</style></title><secondary-title><style face="normal" font="default" size="100%">NPJ Syst Biol Appl</style></secondary-title><alt-title><style face="normal" font="default" size="100%">NPJ Syst Biol Appl</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug discovery</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolic Networks and Pathways</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30854222?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin-Broto, Javier</style></author><author><style face="normal" font="default" size="100%">Stacchiotti, Silvia</style></author><author><style face="normal" font="default" size="100%">Lopez-Pousa, Antonio</style></author><author><style face="normal" font="default" size="100%">Redondo, Andres</style></author><author><style face="normal" font="default" size="100%">Bernabeu, Daniel</style></author><author><style face="normal" font="default" size="100%">de Alava, Enrique</style></author><author><style face="normal" font="default" size="100%">Casali, Paolo G</style></author><author><style face="normal" font="default" size="100%">Italiano, Antoine</style></author><author><style face="normal" font="default" size="100%">Gutierrez, Antonio</style></author><author><style face="normal" font="default" size="100%">Moura, David S</style></author><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Diaz-Martin, Juan</style></author><author><style face="normal" font="default" size="100%">Biscuola, Michele</style></author><author><style face="normal" font="default" size="100%">Taron, Miguel</style></author><author><style face="normal" font="default" size="100%">Collini, Paola</style></author><author><style face="normal" font="default" size="100%">Ranchere-Vince, Dominique</style></author><author><style face="normal" font="default" size="100%">Garcia Del Muro, Xavier</style></author><author><style face="normal" font="default" size="100%">Grignani, Giovanni</style></author><author><style face="normal" font="default" size="100%">Dumont, Sarah</style></author><author><style face="normal" font="default" size="100%">Martinez-Trufero, Javier</style></author><author><style face="normal" font="default" size="100%">Palmerini, Emanuela</style></author><author><style face="normal" font="default" size="100%">Hindi, Nadia</style></author><author><style face="normal" font="default" size="100%">Sebio, Ana</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dei Tos, Angelo Paolo</style></author><author><style face="normal" font="default" size="100%">LeCesne, Axel</style></author><author><style face="normal" font="default" size="100%">Blay, Jean-Yves</style></author><author><style face="normal" font="default" size="100%">Cruz, Josefina</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pazopanib for treatment of advanced malignant and dedifferentiated solitary fibrous tumour: a multicentre, single-arm, phase 2 trial.</style></title><secondary-title><style face="normal" font="default" size="100%">Lancet Oncol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Lancet Oncol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiogenesis Inhibitors</style></keyword><keyword><style  face="normal" font="default" size="100%">Antineoplastic Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Indazoles</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Multivariate Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrimidines</style></keyword><keyword><style  face="normal" font="default" size="100%">Response Evaluation Criteria in Solid Tumors</style></keyword><keyword><style  face="normal" font="default" size="100%">Soft Tissue Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Solitary Fibrous Tumors</style></keyword><keyword><style  face="normal" font="default" size="100%">Sulfonamides</style></keyword><keyword><style  face="normal" font="default" size="100%">Survival Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">134-144</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;A solitary fibrous tumour is a rare soft-tissue tumour with three clinicopathological variants: typical, malignant, and dedifferentiated. Preclinical experiments and retrospective studies have shown different sensitivities of solitary fibrous tumour to chemotherapy and antiangiogenics. We therefore designed a trial to assess the activity of pazopanib in a cohort of patients with malignant or dedifferentiated solitary fibrous tumour. The clinical and translational results are presented here.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;In this single-arm, phase 2 trial, adult patients (aged ≥ 18 years) with histologically confirmed metastatic or unresectable malignant or dedifferentiated solitary fibrous tumour at any location, who had progressed (by RECIST and Choi criteria) in the previous 6 months and had an ECOG performance status of 0-2, were enrolled at 16 third-level hospitals with expertise in sarcoma care in Spain, Italy, and France. Patients received pazopanib 800 mg once daily, taken orally without food, at least 1 h before or 2 h after a meal, until progression or intolerance. The primary endpoint of the study was overall response measured by Choi criteria in the subset of the intention-to-treat population (patients who received at least 1 month of treatment with at least one radiological assessment). All patients who received at least one dose of the study drug were included in the safety analyses. This study is registered with ClinicalTrials.gov, number NCT02066285, and with the European Clinical Trials Database, EudraCT number 2013-005456-15.&lt;/p&gt;&lt;p&gt;&lt;b&gt;FINDINGS: &lt;/b&gt;From June 26, 2014, to Nov 24, 2016, of 40 patients assessed, 36 were enrolled (34 with malignant solitary fibrous tumour and two with dedifferentiated solitary fibrous tumour). Median follow-up was 27 months (IQR 16-31). Based on central radiology review, 18 (51%) of 35 evaluable patients had partial responses, nine (26%) had stable disease, and eight (23%) had progressive disease according to Choi criteria. Further enrolment of patients with dedifferentiated solitary fibrous tumour was stopped after detection of early and fast progressions in a planned interim analysis. 51% (95% CI 34-69) of 35 patients achieved an overall response according to Choi criteria. Ten (29%) of 35 patients died. There were no deaths related to adverse events and the most frequent grade 3 or higher adverse events were hypertension (11 [31%] of 36 patients), neutropenia (four [11%]), increased concentrations of alanine aminotransferase (four [11%]), and increased concentrations of bilirubin (three [8%]).&lt;/p&gt;&lt;p&gt;&lt;b&gt;INTERPRETATION: &lt;/b&gt;To our knowledge, this is the first trial of pazopanib for treatment of malignant solitary fibrous tumour showing activity in this patient group. The manageable toxicity profile and the activity shown by pazopanib suggests that this drug could be an option for systemic treatment of advanced malignant solitary fibrous tumour, and provides a benchmark for future trials.&lt;/p&gt;&lt;p&gt;&lt;b&gt;FUNDING: &lt;/b&gt;Spanish Group for Research on Sarcomas (GEIS), Italian Sarcoma Group (ISG), French Sarcoma Group (FSG), GlaxoSmithKline, and Novartis.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30578023?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Perez-Gil, Daniel</style></author><author><style face="normal" font="default" size="100%">Lopez, Francisco J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Marin-Garcia, Pablo</style></author><author><style face="normal" font="default" size="100%">Rendon, Augusto</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Mar 28</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">159</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTful web service API offered by CellBase. This package offers a fast and user-friendly access to biological information without the need of installing any local database. In addition, a series of command-line tools are provided to perform common bioinformatic tasks, such as variant annotation. CellBase data is always available by a high-availability cluster and queries have been tuned to ensure a real-time performance.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;PyCellBase is an open-source Python package that provides an efficient access to heterogeneous biological information. It allows to perform tasks that require a comprehensive set of knowledge resources, as for example variant annotation. Queries can be easily fine-tuned to retrieve the desired information of particular biological features. PyCellBase offers the convenience of an object-oriented scripting language and provides the ability to integrate the obtained results into other Python applications and pipelines.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30922213?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peña-Chilet, Maria</style></author><author><style face="normal" font="default" size="100%">Esteban-Medina, Marina</style></author><author><style face="normal" font="default" size="100%">Falco, Matias M.</style></author><author><style face="normal" font="default" size="100%">Rian, Kinza</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R.</style></author><author><style face="normal" font="default" size="100%">Loucera, Carlos</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using mechanistic models for the clinical interpretation of complex genomic variation</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific Reports</style></secondary-title><short-title><style face="normal" font="default" size="100%">Sci Rep</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-12-2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/s41598-019-55454-7http://www.nature.com/articles/s41598-019-55454-7.pdfhttp://www.nature.com/articles/s41598-019-55454-7.pdfhttp://www.nature.com/articles/s41598-019-55454-7</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">9</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ferreira, Pedro G</style></author><author><style face="normal" font="default" size="100%">Muñoz-Aguirre, Manuel</style></author><author><style face="normal" font="default" size="100%">Reverter, Ferran</style></author><author><style face="normal" font="default" size="100%">Sá Godinho, Caio P</style></author><author><style face="normal" font="default" size="100%">Sousa, Abel</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">Sodaei, Reza</style></author><author><style face="normal" font="default" size="100%">Hidalgo, Marta R</style></author><author><style face="normal" font="default" size="100%">Pervouchine, Dmitri</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Nurtdinov, Ramil</style></author><author><style face="normal" font="default" size="100%">Breschi, Alessandra</style></author><author><style face="normal" font="default" size="100%">Amador, Raziel</style></author><author><style face="normal" font="default" size="100%">Oliveira, Patrícia</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Curado, João</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Oliveira, Carla</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Sammeth, Michael</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The effects of death and post-mortem cold ischemia on human tissue transcriptomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Blood</style></keyword><keyword><style  face="normal" font="default" size="100%">Cold Ischemia</style></keyword><keyword><style  face="normal" font="default" size="100%">Death</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">gene expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Postmortem Changes</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Stochastic Processes</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Feb 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">490</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29440659?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">López, M</style></author><author><style face="normal" font="default" size="100%">Rueda, A</style></author><author><style face="normal" font="default" size="100%">Florido, J P</style></author><author><style face="normal" font="default" size="100%">Blasco, L</style></author><author><style face="normal" font="default" size="100%">Fernández-García, L</style></author><author><style face="normal" font="default" size="100%">Trastoy, R</style></author><author><style face="normal" font="default" size="100%">Fernández-Cuenca, F</style></author><author><style face="normal" font="default" size="100%">Martínez-Martínez, L</style></author><author><style face="normal" font="default" size="100%">Vila, J</style></author><author><style face="normal" font="default" size="100%">Pascual, A</style></author><author><style face="normal" font="default" size="100%">Bou, G</style></author><author><style face="normal" font="default" size="100%">Tomas, M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolution of the Quorum network and the mobilome (plasmids and bacteriophages) in clinical strains of Acinetobacter baumannii during a decade.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acinetobacter baumannii</style></keyword><keyword><style  face="normal" font="default" size="100%">Acinetobacter Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteriophages</style></keyword><keyword><style  face="normal" font="default" size="100%">Cross Infection</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Plasmids</style></keyword><keyword><style  face="normal" font="default" size="100%">Quorum Sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrospective Studies</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Feb 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">2523</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this study, we compared eighteen clinical strains of A. baumannii belonging to the ST-2 clone and isolated from patients in the same intensive care unit (ICU) in 2000 (9 strains referred to collectively as Ab_GEIH-2000) and 2010 (9 strains referred to collectively as Ab_GEIH-2010), during the GEIH-REIPI project (Umbrella BioProject PRJNA422585). We observed two main molecular differences between the Ab_GEIH-2010 and the Ab_GEIH-2000 collections, acquired over the course of the decade long sampling interval and involving the mobilome: i) a plasmid harbouring genes for bla ß-lactamase and abKA/abkB proteins of a toxin-antitoxin system; and ii) two temperate bacteriophages, Ab105-1ϕ (63 proteins) and Ab105-2ϕ (93 proteins), containing important viral defence proteins. Moreover, all Ab_GEIH-2010 strains contained a Quorum functional network of Quorum Sensing (QS) and Quorum Quenching (QQ) mechanisms, including a new QQ enzyme, AidA, which acts as a bacterial defence mechanism against the exogenous 3-oxo-C12-HSL. Interestingly, the infective capacity of the bacteriophages isolated in this study (Ab105-1ϕ and Ab105-2ϕ) was higher in the Ab_GEIH-2010 strains (carrying a functional Quorum network) than in the Ab_GEIH-2000 strains (carrying a deficient Quorum network), in which the bacteriophages showed little or no infectivity. This is the first study about the evolution of the Quorum network and the mobilome in clinical strains of Acinetobacter baumannii during a decade.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29410443?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rodríguez Hernáez, Javier</style></author><author><style face="normal" font="default" size="100%">Cerón Cucchi, Maria Esperanza</style></author><author><style face="normal" font="default" size="100%">Cravero, Silvio</style></author><author><style face="normal" font="default" size="100%">Martinez, Maria Carolina</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Sergio</style></author><author><style face="normal" font="default" size="100%">Puebla, Andrea</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Farber, Marisa</style></author><author><style face="normal" font="default" size="100%">Paniego, Norma</style></author><author><style face="normal" font="default" size="100%">Rivarola, Máximo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The first complete genomic structure of Butyrivibrio fibrisolvens and its chromid.</style></title><secondary-title><style face="normal" font="default" size="100%">Microb Genom</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Microb Genom</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Butyrivibrio fibrisolvens</style></keyword><keyword><style  face="normal" font="default" size="100%">Cattle</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Milk</style></keyword><keyword><style  face="normal" font="default" size="100%">Rumen</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Butyrivibrio fibrisolvens forms part of the gastrointestinal microbiome of ruminants and other mammals, including humans. Indeed, it is one of the most common bacteria found in the rumen and plays an important role in ruminal fermentation of polysaccharides, yet, to date, there is no closed reference genome published for this species in any ruminant animal. We successfully assembled the nearly complete genome sequence of B. fibrisolvens strain INBov1 isolated from cow rumen using Illumina paired-end reads, 454 Roche single-end and mate pair sequencing technology. Additionally, we constructed an optical restriction map of this strain to aid in scaffold ordering and positioning, and completed the first genomic structure of this species. Moreover, we identified and assembled the first chromid of this species (pINBov266). The INBov1 genome encodes a large set of genes involved in the cellulolytic process but lacks key genes. This seems to indicate that B. fibrisolvens plays an important role in ruminal cellulolytic processes, but does not have autonomous cellulolytic capacity. When searching for genes involved in the biohydrogenation of unsaturated fatty acids, no linoleate isomerase gene was found in this strain. INBov1 does encode oleate hydratase genes known to participate in the hydrogenation of oleic acids. Furthermore, INBov1 contains an enolase gene, which has been recently determined to participate in the synthesis of conjugated linoleic acids. This work confirms the presence of a novel chromid in B. fibrisolvens and provides a new potential reference genome sequence for this species, providing new insight into its role in biohydrogenation and carbohydrate degradation.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30216146?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wu, Guohong Albert</style></author><author><style face="normal" font="default" size="100%">Terol, Javier</style></author><author><style face="normal" font="default" size="100%">Ibañez, Victoria</style></author><author><style face="normal" font="default" size="100%">López-García, Antonio</style></author><author><style face="normal" font="default" size="100%">Pérez-Román, Estela</style></author><author><style face="normal" font="default" size="100%">Borredá, Carles</style></author><author><style face="normal" font="default" size="100%">Domingo, Concha</style></author><author><style face="normal" font="default" size="100%">Tadeo, Francisco R</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Alonso, Roberto</style></author><author><style face="normal" font="default" size="100%">Curk, Franck</style></author><author><style face="normal" font="default" size="100%">Du, Dongliang</style></author><author><style face="normal" font="default" size="100%">Ollitrault, Patrick</style></author><author><style face="normal" font="default" size="100%">Roose, Mikeal L</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Gmitter, Frederick G</style></author><author><style face="normal" font="default" size="100%">Rokhsar, Daniel S</style></author><author><style face="normal" font="default" size="100%">Talon, Manuel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomics of the origin and evolution of Citrus.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Asia, Southeastern</style></keyword><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">citrus</style></keyword><keyword><style  face="normal" font="default" size="100%">Crop Production</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Speciation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Heterozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">History, Ancient</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Migration</style></keyword><keyword><style  face="normal" font="default" size="100%">Hybridization, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Feb 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">554</style></volume><pages><style face="normal" font="default" size="100%">311-316</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The genus Citrus, comprising some of the most widely cultivated fruit crops worldwide, includes an uncertain number of species. Here we describe ten natural citrus species, using genomic, phylogenetic and biogeographic analyses of 60 accessions representing diverse citrus germ plasms, and propose that citrus diversified during the late Miocene epoch through a rapid southeast Asian radiation that correlates with a marked weakening of the monsoons. A second radiation enabled by migration across the Wallace line gave rise to the Australian limes in the early Pliocene epoch. Further identification and analyses of hybrids and admixed genomes provides insights into the genealogy of major commercial cultivars of citrus. Among mandarins and sweet orange, we find an extensive network of relatedness that illuminates the domestication of these groups. Widespread pummelo admixture among these mandarins and its correlation with fruit size and acidity suggests a plausible role of pummelo introgression in the selection of palatable mandarins. This work provides a new evolutionary framework for the genus Citrus.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7692</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29414943?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cobo-Vuilleumier, Nadia</style></author><author><style face="normal" font="default" size="100%">Lorenzo, Petra I</style></author><author><style face="normal" font="default" size="100%">Rodríguez, Noelia García</style></author><author><style face="normal" font="default" size="100%">Herrera Gómez, Irene de Gracia</style></author><author><style face="normal" font="default" size="100%">Fuente-Martin, Esther</style></author><author><style face="normal" font="default" size="100%">López-Noriega, Livia</style></author><author><style face="normal" font="default" size="100%">Mellado-Gil, José Manuel</style></author><author><style face="normal" font="default" size="100%">Romero-Zerbo, Silvana-Yanina</style></author><author><style face="normal" font="default" size="100%">Baquié, Mathurin</style></author><author><style face="normal" font="default" size="100%">Lachaud, Christian Claude</style></author><author><style face="normal" font="default" size="100%">Stifter, Katja</style></author><author><style face="normal" font="default" size="100%">Perdomo, German</style></author><author><style face="normal" font="default" size="100%">Bugliani, Marco</style></author><author><style face="normal" font="default" size="100%">De Tata, Vincenzo</style></author><author><style face="normal" font="default" size="100%">Bosco, Domenico</style></author><author><style face="normal" font="default" size="100%">Parnaud, Geraldine</style></author><author><style face="normal" font="default" size="100%">Pozo, David</style></author><author><style face="normal" font="default" size="100%">Hmadcha, Abdelkrim</style></author><author><style face="normal" font="default" size="100%">Florido, Javier P</style></author><author><style face="normal" font="default" size="100%">Toscano, Miguel G</style></author><author><style face="normal" font="default" size="100%">de Haan, Peter</style></author><author><style face="normal" font="default" size="100%">Schoonjans, Kristina</style></author><author><style face="normal" font="default" size="100%">Sánchez Palazón, Luis</style></author><author><style face="normal" font="default" size="100%">Marchetti, Piero</style></author><author><style face="normal" font="default" size="100%">Schirmbeck, Reinhold</style></author><author><style face="normal" font="default" size="100%">Martín-Montalvo, Alejandro</style></author><author><style face="normal" font="default" size="100%">Meda, Paolo</style></author><author><style face="normal" font="default" size="100%">Soria, Bernat</style></author><author><style face="normal" font="default" size="100%">Bermúdez-Silva, Francisco-Javier</style></author><author><style face="normal" font="default" size="100%">St-Onge, Luc</style></author><author><style face="normal" font="default" size="100%">Gauthier, Benoit R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">LRH-1 agonism favours an immune-islet dialogue which protects against diabetes mellitus.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Apoptosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Communication</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Survival</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes Mellitus, Experimental</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes Mellitus, Type 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hypoglycemic Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Immunity, Innate</style></keyword><keyword><style  face="normal" font="default" size="100%">insulin</style></keyword><keyword><style  face="normal" font="default" size="100%">Insulin-Secreting Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Islets of Langerhans</style></keyword><keyword><style  face="normal" font="default" size="100%">Islets of Langerhans Transplantation</style></keyword><keyword><style  face="normal" font="default" size="100%">Macrophages</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Inbred C57BL</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenalenes</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptors, Cytoplasmic and Nuclear</style></keyword><keyword><style  face="normal" font="default" size="100%">Streptozocin</style></keyword><keyword><style  face="normal" font="default" size="100%">T-Lymphocytes, Regulatory</style></keyword><keyword><style  face="normal" font="default" size="100%">Transplantation, Heterologous</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Apr 16</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">1488</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Type 1 diabetes mellitus (T1DM) is due to the selective destruction of islet beta cells by immune cells. Current therapies focused on repressing the immune attack or stimulating beta cell regeneration still have limited clinical efficacy. Therefore, it is timely to identify innovative targets to dampen the immune process, while promoting beta cell survival and function. Liver receptor homologue-1 (LRH-1) is a nuclear receptor that represses inflammation in digestive organs, and protects pancreatic islets against apoptosis. Here, we show that BL001, a small LRH-1 agonist, impedes hyperglycemia progression and the immune-dependent inflammation of pancreas in murine models of T1DM, and beta cell apoptosis in islets of type 2 diabetic patients, while increasing beta cell mass and insulin secretion. Thus, we suggest that LRH-1 agonism favors a dialogue between immune and islet cells, which could be druggable to protect against diabetes mellitus.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29662071?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gonzalez, Sergio</style></author><author><style face="normal" font="default" size="100%">Clavijo, Bernardo</style></author><author><style face="normal" font="default" size="100%">Rivarola, Máximo</style></author><author><style face="normal" font="default" size="100%">Moreno, Patricio</style></author><author><style face="normal" font="default" size="100%">Fernandez, Paula</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Paniego, Norma</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Feb 22</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">121</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net .&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28222698?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Roca-Ayats, Neus</style></author><author><style face="normal" font="default" size="100%">Balcells, Susana</style></author><author><style face="normal" font="default" size="100%">Garcia-Giralt, Natàlia</style></author><author><style face="normal" font="default" size="100%">Falcó-Mascaró, Maite</style></author><author><style face="normal" font="default" size="100%">Martínez-Gil, Núria</style></author><author><style face="normal" font="default" size="100%">Abril, Josep F</style></author><author><style face="normal" font="default" size="100%">Urreizti, Roser</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Quesada-Gómez, José M</style></author><author><style face="normal" font="default" size="100%">Nogués, Xavier</style></author><author><style face="normal" font="default" size="100%">Mellibovsky, Leonardo</style></author><author><style face="normal" font="default" size="100%">Prieto-Alhambra, Daniel</style></author><author><style face="normal" font="default" size="100%">Dunford, James E</style></author><author><style face="normal" font="default" size="100%">Javaid, Muhammad K</style></author><author><style face="normal" font="default" size="100%">Russell, R Graham</style></author><author><style face="normal" font="default" size="100%">Grinberg, Daniel</style></author><author><style face="normal" font="default" size="100%">Díez-Pérez, Adolfo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.</style></title><secondary-title><style face="normal" font="default" size="100%">N Engl J Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">N Engl J Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Bone Density Conservation Agents</style></keyword><keyword><style  face="normal" font="default" size="100%">Dimethylallyltranstransferase</style></keyword><keyword><style  face="normal" font="default" size="100%">Diphosphonates</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Farnesyltranstransferase</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Femoral Fractures</style></keyword><keyword><style  face="normal" font="default" size="100%">Geranyltranstransferase</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 May 04</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nejm.org/doi/full/10.1056/NEJMc1612804</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">376</style></volume><pages><style face="normal" font="default" size="100%">1794-1795</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">18</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28467865?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lopez, Javier</style></author><author><style face="normal" font="default" size="100%">Coll, Jacobo</style></author><author><style face="normal" font="default" size="100%">Haimel, Matthias</style></author><author><style face="normal" font="default" size="100%">Kandasamy, Swaathi</style></author><author><style face="normal" font="default" size="100%">Tárraga, Joaquín</style></author><author><style face="normal" font="default" size="100%">Furio-Tari, Pedro</style></author><author><style face="normal" font="default" size="100%">Bari, Wasim</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Gräf, Stefan</style></author><author><style face="normal" font="default" size="100%">Rendon, Augusto</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HGVA: the Human Genome Variation Archive.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jul 03</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx445</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">45</style></volume><pages><style face="normal" font="default" size="100%">W189-W194</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">W1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28535294?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moschen, Sebastián</style></author><author><style face="normal" font="default" size="100%">Di Rienzo, Julio A</style></author><author><style face="normal" font="default" size="100%">Higgins, Janet</style></author><author><style face="normal" font="default" size="100%">Tohge, Takayuki</style></author><author><style face="normal" font="default" size="100%">Watanabe, Mutsumi</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Sergio</style></author><author><style face="normal" font="default" size="100%">Rivarola, Máximo</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Hopp, H Esteban</style></author><author><style face="normal" font="default" size="100%">Hoefgen, Rainer</style></author><author><style face="normal" font="default" size="100%">Fernie, Alisdair R</style></author><author><style face="normal" font="default" size="100%">Paniego, Norma</style></author><author><style face="normal" font="default" size="100%">Fernandez, Paula</style></author><author><style face="normal" font="default" size="100%">Heinz, Ruth A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Mol Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Plant Mol Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chlorophyll</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Helianthus</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Array Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Stress, Physiological</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Water</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">94</style></volume><pages><style face="normal" font="default" size="100%">549-564</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;By integration of transcriptional and metabolic profiles we identified pathways and hubs transcription factors regulated during drought conditions in sunflower, useful for applications in molecular and/or biotechnological breeding. Drought is one of the most important environmental stresses that effects crop productivity in many agricultural regions. Sunflower is tolerant to drought conditions but the mechanisms involved in this tolerance remain unclear at the molecular level. The aim of this study was to characterize and integrate transcriptional and metabolic pathways related to drought stress in sunflower plants, by using a system biology approach. Our results showed a delay in plant senescence with an increase in the expression level of photosynthesis related genes as well as higher levels of sugars, osmoprotectant amino acids and ionic nutrients under drought conditions. In addition, we identified transcription factors that were upregulated during drought conditions and that may act as hubs in the transcriptional network. Many of these transcription factors belong to families implicated in the drought response in model species. The integration of transcriptomic and metabolomic data in this study, together with physiological measurements, has improved our understanding of the biological responses during droughts and contributes to elucidate the molecular mechanisms involved under this environmental condition. These findings will provide useful biotechnological tools to improve stress tolerance while maintaining crop yield under restricted water availability.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4-5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28639116?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Matalonga, Leslie</style></author><author><style face="normal" font="default" size="100%">Bravo, Miren</style></author><author><style face="normal" font="default" size="100%">Serra-Peinado, Carla</style></author><author><style face="normal" font="default" size="100%">García-Pelegrí, Elisabeth</style></author><author><style face="normal" font="default" size="100%">Ugarteburu, Olatz</style></author><author><style face="normal" font="default" size="100%">Vidal, Silvia</style></author><author><style face="normal" font="default" size="100%">Llambrich, Maria</style></author><author><style face="normal" font="default" size="100%">Quintana, Ester</style></author><author><style face="normal" font="default" size="100%">Fuster-Jorge, Pedro</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Bravo, Maria Nieves</style></author><author><style face="normal" font="default" size="100%">Beltran, Sergi</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Foulquier, François</style></author><author><style face="normal" font="default" size="100%">Matthijs, Gert</style></author><author><style face="normal" font="default" size="100%">Mills, Philippa</style></author><author><style face="normal" font="default" size="100%">Ribes, Antonia</style></author><author><style face="normal" font="default" size="100%">Egea, Gustavo</style></author><author><style face="normal" font="default" size="100%">Briones, Paz</style></author><author><style face="normal" font="default" size="100%">Tort, Frederic</style></author><author><style face="normal" font="default" size="100%">Girós, Marisa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mutations in TRAPPC11 are associated with a congenital disorder of glycosylation.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Abnormalities, Multiple</style></keyword><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Congenital Disorders of Glycosylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Vesicular Transport Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">38</style></volume><pages><style face="normal" font="default" size="100%">148-151</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Congenital disorders of glycosylation (CDG) are a heterogeneous and rapidly growing group of diseases caused by abnormal glycosylation of proteins and/or lipids. Mutations in genes involved in the homeostasis of the endoplasmic reticulum (ER), the Golgi apparatus (GA), and the vesicular trafficking from the ER to the ER-Golgi intermediate compartment (ERGIC) have been found to be associated with CDG. Here, we report a patient with defects in both N- and O-glycosylation combined with a delayed vesicular transport in the GA due to mutations in TRAPPC11, a subunit of the TRAPPIII complex. TRAPPIII is implicated in the anterograde transport from the ER to the ERGIC as well as in the vesicle export from the GA. This report expands the spectrum of genetic alterations associated with CDG, providing new insights for the diagnosis and the understanding of the physiopathological mechanisms underlying glycosylation disorders.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27862579?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Schriemer, Duco</style></author><author><style face="normal" font="default" size="100%">Cheng, William W</style></author><author><style face="normal" font="default" size="100%">Chauhan, Rajendra K</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Berrios, Courtney</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Brooks, Alice S</style></author><author><style face="normal" font="default" size="100%">Brouwer, Rutger W W</style></author><author><style face="normal" font="default" size="100%">Burns, Alan J</style></author><author><style face="normal" font="default" size="100%">Cherny, Stacey S</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Eggen, Bart J L</style></author><author><style face="normal" font="default" size="100%">Griseri, Paola</style></author><author><style face="normal" font="default" size="100%">Jalloh, Binta</style></author><author><style face="normal" font="default" size="100%">Le, Thuy-Linh</style></author><author><style face="normal" font="default" size="100%">Lui, Vincent C H</style></author><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Matera, Ivana</style></author><author><style face="normal" font="default" size="100%">Ngan, Elly S W</style></author><author><style face="normal" font="default" size="100%">Pelet, Anna</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Sham, Pak C</style></author><author><style face="normal" font="default" size="100%">Shepherd, Iain T</style></author><author><style face="normal" font="default" size="100%">So, Man-Ting</style></author><author><style face="normal" font="default" size="100%">Sribudiani, Yunia</style></author><author><style face="normal" font="default" size="100%">Tang, Clara S M</style></author><author><style face="normal" font="default" size="100%">van den Hout, Mirjam C G N</style></author><author><style face="normal" font="default" size="100%">van der Linde, Herma C</style></author><author><style face="normal" font="default" size="100%">van Ham, Tjakko J</style></author><author><style face="normal" font="default" size="100%">van IJcken, Wilfred F J</style></author><author><style face="normal" font="default" size="100%">Verheij, Joke B G M</style></author><author><style face="normal" font="default" size="100%">Amiel, Jeanne</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Ceccherini, Isabella</style></author><author><style face="normal" font="default" size="100%">Chakravarti, Aravinda</style></author><author><style face="normal" font="default" size="100%">Lyonnet, Stanislas</style></author><author><style face="normal" font="default" size="100%">Tam, Paul K H</style></author><author><style face="normal" font="default" size="100%">Garcia-Barceló, Maria-Mercè</style></author><author><style face="normal" font="default" size="100%">Hofstra, Robert Mw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome biology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Hirschprung</style></keyword><keyword><style  face="normal" font="default" size="100%">Rare Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">WES</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Mar 08</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1174-6</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">48</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Hirschsprung disease (HSCR), which is congenital obstruction of the bowel, results from a failure of enteric nervous system (ENS) progenitors to migrate, proliferate, differentiate, or survive within the distal intestine. Previous studies that have searched for genes underlying HSCR have focused on ENS-related pathways and genes not fitting the current knowledge have thus often been ignored. We identify and validate novel HSCR genes using whole exome sequencing (WES), burden tests, in silico prediction, unbiased in vivo analyses of the mutated genes in zebrafish, and expression analyses in zebrafish, mouse, and human. RESULTS: We performed de novo mutation (DNM) screening on 24 HSCR trios. We identify 28 DNMs in 21 different genes. Eight of the DNMs we identified occur in RET, the main HSCR gene, and the remaining 20 DNMs reside in genes not reported in the ENS. Knockdown of all 12 genes with missense or loss-of-function DNMs showed that the orthologs of four genes (DENND3, NCLN, NUP98, and TBATA) are indispensable for ENS development in zebrafish, and these results were confirmed by CRISPR knockout. These genes are also expressed in human and mouse gut and/or ENS progenitors. Importantly, the encoded proteins are linked to neuronal processes shared by the central nervous system and the ENS. CONCLUSIONS: Our data open new fields of investigation into HSCR pathology and provide novel insights into the development of the ENS. Moreover, the study demonstrates that functional analyses of genes carrying DNMs are warranted to delineate the full genetic architecture of rare complex diseases.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Schriemer, Duco</style></author><author><style face="normal" font="default" size="100%">Cheng, William W.</style></author><author><style face="normal" font="default" size="100%">Chauhan, Rajendra K.</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Berrios, Courtney</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Brooks, Alice S.</style></author><author><style face="normal" font="default" size="100%">Brouwer, Rutger W. W.</style></author><author><style face="normal" font="default" size="100%">Burns, Alan J.</style></author><author><style face="normal" font="default" size="100%">Cherny, Stacey S.</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Eggen, Bart J. L.</style></author><author><style face="normal" font="default" size="100%">Griseri, Paola</style></author><author><style face="normal" font="default" size="100%">Jalloh, Binta</style></author><author><style face="normal" font="default" size="100%">Le, Thuy-Linh</style></author><author><style face="normal" font="default" size="100%">Lui, Vincent C. H.</style></author><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Matera, Ivana</style></author><author><style face="normal" font="default" size="100%">Ngan, Elly S. W.</style></author><author><style face="normal" font="default" size="100%">Pelet, Anna</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Sham, Pak C.</style></author><author><style face="normal" font="default" size="100%">Shepherd, Iain T.</style></author><author><style face="normal" font="default" size="100%">So, Man-Ting</style></author><author><style face="normal" font="default" size="100%">Sribudiani, Yunia</style></author><author><style face="normal" font="default" size="100%">Tang, Clara S. M.</style></author><author><style face="normal" font="default" size="100%">van den Hout, Mirjam C. G. N.</style></author><author><style face="normal" font="default" size="100%">van der Linde, Herma C.</style></author><author><style face="normal" font="default" size="100%">van Ham, Tjakko J.</style></author><author><style face="normal" font="default" size="100%">van IJcken, Wilfred F. J.</style></author><author><style face="normal" font="default" size="100%">Verheij, Joke B. G. M.</style></author><author><style face="normal" font="default" size="100%">Amiel, Jeanne</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Ceccherini, Isabella</style></author><author><style face="normal" font="default" size="100%">Chakravarti, Aravinda</style></author><author><style face="normal" font="default" size="100%">Lyonnet, Stanislas</style></author><author><style face="normal" font="default" size="100%">Tam, Paul K. H.</style></author><author><style face="normal" font="default" size="100%">Garcia-Barceló, Maria-Mercè</style></author><author><style face="normal" font="default" size="100%">Hofstra, Robert M. W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biology</style></secondary-title><short-title><style face="normal" font="default" size="100%">Genome Biol</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-12-2017</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1174-6http://link.springer.com/content/pdf/10.1186/s13059-017-1174-6.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Amadoz, Alicia</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Alemán, Alejandro</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Rodriguez, Juan A</style></author><author><style face="normal" font="default" size="100%">Daub, Josephine T</style></author><author><style face="normal" font="default" size="100%">Muntané, Gerard</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Florido, Javier P</style></author><author><style face="normal" font="default" size="100%">Arce, Pablo</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Arnold, Todd E</style></author><author><style face="normal" font="default" size="100%">Spleiss, Olivia</style></author><author><style face="normal" font="default" size="100%">Alvarez-Tejado, Miguel</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Shomi S</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">267 Spanish exomes reveal population-specific differences in disease-related genetic variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular biology and evolution</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">disease</style></keyword><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">polymorphisms</style></keyword><keyword><style  face="normal" font="default" size="100%">Population genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">prioritization</style></keyword><keyword><style  face="normal" font="default" size="100%">SNP</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan 13</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://mbe.oxfordjournals.org/content/early/2016/02/17/molbev.msw005.full</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalogue of local variability motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including about 10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies in order to distinguish real disease associations from population-specific polymorphisms.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lagarde, Julien</style></author><author><style face="normal" font="default" size="100%">Uszczynska-Ratajczak, Barbara</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Jose Manuel</style></author><author><style face="normal" font="default" size="100%">Tapanari, Electra</style></author><author><style face="normal" font="default" size="100%">Mudge, Jonathan M.</style></author><author><style face="normal" font="default" size="100%">Steward, Charles A.</style></author><author><style face="normal" font="default" size="100%">Wilming, Laurens</style></author><author><style face="normal" font="default" size="100%">Tanzer, Andrea</style></author><author><style face="normal" font="default" size="100%">Howald, Cédric</style></author><author><style face="normal" font="default" size="100%">Chrast, Jacqueline</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Lopez-Domingo, Francisco J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Reymond, Alexandre</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Harrow, Jennifer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq)</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Communications</style></secondary-title><short-title><style face="normal" font="default" size="100%">Nat Commun</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-11-2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/ncomms12339http://www.nature.com/articles/ncomms12339.pdfhttp://www.nature.com/articles/ncomms12339.pdfhttp://www.nature.com/articles/ncomms12339</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lagarde, Julien</style></author><author><style face="normal" font="default" size="100%">Uszczynska-Ratajczak, Barbara</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Jose Manuel</style></author><author><style face="normal" font="default" size="100%">Tapanari, Electra</style></author><author><style face="normal" font="default" size="100%">Mudge, Jonathan M</style></author><author><style face="normal" font="default" size="100%">Steward, Charles A</style></author><author><style face="normal" font="default" size="100%">Wilming, Laurens</style></author><author><style face="normal" font="default" size="100%">Tanzer, Andrea</style></author><author><style face="normal" font="default" size="100%">Howald, Cédric</style></author><author><style face="normal" font="default" size="100%">Chrast, Jacqueline</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Reymond, Alexandre</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Harrow, Jennifer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq).</style></title><secondary-title><style face="normal" font="default" size="100%">Nature communications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/ncomms12339</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">12339</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Long non-coding RNAs (lncRNAs) constitute a large, yet mostly uncharacterized fraction of the mammalian transcriptome. Such characterization requires a comprehensive, high-quality annotation of their gene structure and boundaries, which is currently lacking. Here we describe RACE-Seq, an experimental workflow designed to address this based on RACE (rapid amplification of cDNA ends) and long-read RNA sequencing. We apply RACE-Seq to 398 human lncRNA genes in seven tissues, leading to the discovery of 2,556 on-target, novel transcripts. About 60% of the targeted loci are extended in either 5’ or 3’, often reaching genomic hallmarks of gene boundaries. Analysis of the novel transcripts suggests that lncRNAs are as long, have as many exons and undergo as much alternative splicing as protein-coding genes, contrary to current assumptions. Overall, we show that RACE-Seq is an effective tool to annotate an organism’s deep transcriptome, and compares favourably to other targeted sequencing techniques.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sanchez-Mut, J V</style></author><author><style face="normal" font="default" size="100%">Heyn, H</style></author><author><style face="normal" font="default" size="100%">Vidal, E</style></author><author><style face="normal" font="default" size="100%">Moran, S</style></author><author><style face="normal" font="default" size="100%">Sayols, S</style></author><author><style face="normal" font="default" size="100%">Delgado-Morales, R</style></author><author><style face="normal" font="default" size="100%">Schultz, M D</style></author><author><style face="normal" font="default" size="100%">Ansoleaga, B</style></author><author><style face="normal" font="default" size="100%">Garcia-Esparcia, P</style></author><author><style face="normal" font="default" size="100%">Pons-Espinal, M</style></author><author><style face="normal" font="default" size="100%">de Lagran, M M</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Rabano, A</style></author><author><style face="normal" font="default" size="100%">Avila, J</style></author><author><style face="normal" font="default" size="100%">Dierssen, M</style></author><author><style face="normal" font="default" size="100%">Lott, I</style></author><author><style face="normal" font="default" size="100%">Ferrer, I</style></author><author><style face="normal" font="default" size="100%">Ecker, J R</style></author><author><style face="normal" font="default" size="100%">Esteller, M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns.</style></title><secondary-title><style face="normal" font="default" size="100%">Transl Psychiatry</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Transl Psychiatry</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Methylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">neurodegenerative diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Prefrontal Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Tissue Array Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan 19</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e718</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Different neurodegenerative disorders often show similar lesions, such as the presence of amyloid plaques, TAU-neurotangles and synuclein inclusions. The genetically inherited forms are rare, so we wondered whether shared epigenetic aberrations, such as those affecting DNA methylation, might also exist. The studied samples were gray matter samples from the prefrontal cortex of control and neurodegenerative disease-associated cases. We performed the DNA methylation analyses of Alzheimer's disease, dementia with Lewy bodies, Parkinson's disease and Alzheimer-like neurodegenerative profile associated with Down's syndrome samples. The DNA methylation landscapes obtained show that neurodegenerative diseases share similar aberrant CpG methylation shifts targeting a defined gene set. Our findings suggest that neurodegenerative disorders might have similar pathogenetic mechanisms that subsequently evolve into different clinical entities. The identified aberrant DNA methylation changes can be used as biomarkers of the disorders and as potential new targets for the development of new therapies. &lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26784972?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Corton, M</style></author><author><style face="normal" font="default" size="100%">Avila-Fernández, A</style></author><author><style face="normal" font="default" size="100%">Campello, L</style></author><author><style face="normal" font="default" size="100%">Sánchez, M</style></author><author><style face="normal" font="default" size="100%">Benavides, B</style></author><author><style face="normal" font="default" size="100%">López-Molina, M I</style></author><author><style face="normal" font="default" size="100%">Fernández-Sánchez, L</style></author><author><style face="normal" font="default" size="100%">Sánchez-Alcudia, R</style></author><author><style face="normal" font="default" size="100%">da Silva, L R J</style></author><author><style face="normal" font="default" size="100%">Reyes, N</style></author><author><style face="normal" font="default" size="100%">Martín-Garrido, E</style></author><author><style face="normal" font="default" size="100%">Zurita, O</style></author><author><style face="normal" font="default" size="100%">Fernández-San José, P</style></author><author><style face="normal" font="default" size="100%">Pérez-Carro, R</style></author><author><style face="normal" font="default" size="100%">García-García, F</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">García-Sandoval, B</style></author><author><style face="normal" font="default" size="100%">Cuenca, N</style></author><author><style face="normal" font="default" size="100%">Ayuso, C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Co-Repressor Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Codon, Nonsense</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Comparative Genomic Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">Consanguinity</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Eye Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Recessive</style></keyword><keyword><style  face="normal" font="default" size="100%">Homeodomain Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Homozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Interaction Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Retina</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Dystrophies</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Rod Photoreceptor Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trans-Activators</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Oct 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">35370</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis pigmentosa (RP), the most frequent form of inherited retinal dystrophy is characterized by progressive photoreceptor degeneration. Many genes have been implicated in RP development, but several others remain to be identified. Using a combination of homozygosity mapping, whole-exome and targeted next-generation sequencing, we found a novel homozygous nonsense mutation in SAMD11 in five individuals diagnosed with adult-onset RP from two unrelated consanguineous Spanish families. SAMD11 is ortholog to the mouse major retinal SAM domain (mr-s) protein that is implicated in CRX-mediated transcriptional regulation in the retina. Accordingly, protein-protein network analysis revealed a significant interaction of SAMD11 with CRX. Immunoblotting analysis confirmed strong expression of SAMD11 in human retina. Immunolocalization studies revealed SAMD11 was detected in the three nuclear layers of the human retina and interestingly differential expression between cone and rod photoreceptors was observed. Our study strongly implicates SAMD11 as novel cause of RP playing an important role in the pathogenesis of human degeneration of photoreceptors.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27734943?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bravo-Gil, Nereida</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Romero-Pérez, Laura</style></author><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Rodríguez-de la Rúa, Enrique</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving the management of Inherited Retinal Dystrophies by targeted sequencing of a population-specific gene panel.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Eye Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Library</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Heterogeneity</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Therapy</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Dystrophies</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Apr 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">23910</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Next-generation sequencing (NGS) has overcome important limitations to the molecular diagnosis of Inherited Retinal Dystrophies (IRD) such as the high clinical and genetic heterogeneity and the overlapping phenotypes. The purpose of this study was the identification of the genetic defect in 32 Spanish families with different forms of IRD. With that aim, we implemented a custom NGS panel comprising 64 IRD-associated genes in our population, and three disease-associated intronic regions. A total of 37 pathogenic mutations (14 novels) were found in 73% of IRD patients ranging from 50% for autosomal dominant cases, 75% for syndromic cases, 83% for autosomal recessive cases, and 100% for X-linked cases. Additionally, unexpected phenotype-genotype correlations were found in 6 probands, which led to the refinement of their clinical diagnoses. Furthermore, intra- and interfamilial phenotypic variability was observed in two cases. Moreover, two cases unsuccessfully analysed by exome sequencing were resolved by applying this panel. Our results demonstrate that this hypothesis-free approach based on frequently mutated, population-specific loci is highly cost-efficient for the routine diagnosis of this heterogeneous condition and allows the unbiased analysis of a miscellaneous cohort. The molecular information found here has aid clinical diagnosis and has improved genetic counselling and patient management. &lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27032803?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moschen, Sebastián</style></author><author><style face="normal" font="default" size="100%">Bengoa Luoni, Sofía</style></author><author><style face="normal" font="default" size="100%">Di Rienzo, Julio A</style></author><author><style face="normal" font="default" size="100%">Caro, María Del Pilar</style></author><author><style face="normal" font="default" size="100%">Tohge, Takayuki</style></author><author><style face="normal" font="default" size="100%">Watanabe, Mutsumi</style></author><author><style face="normal" font="default" size="100%">Hollmann, Julien</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Sergio</style></author><author><style face="normal" font="default" size="100%">Rivarola, Máximo</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Hopp, Horacio Esteban</style></author><author><style face="normal" font="default" size="100%">Hoefgen, Rainer</style></author><author><style face="normal" font="default" size="100%">Fernie, Alisdair R</style></author><author><style face="normal" font="default" size="100%">Paniego, Norma</style></author><author><style face="normal" font="default" size="100%">Fernandez, Paula</style></author><author><style face="normal" font="default" size="100%">Heinz, Ruth A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Biotechnol J</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Plant Biotechnol J</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Gas Chromatography-Mass Spectrometry</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene ontology</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Helianthus</style></keyword><keyword><style  face="normal" font="default" size="100%">Ions</style></keyword><keyword><style  face="normal" font="default" size="100%">metabolomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Principal Component Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">719-34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Leaf senescence is a complex process, which has dramatic consequences on crop yield. In sunflower, gap between potential and actual yields reveals the economic impact of senescence. Indeed, sunflower plants are incapable of maintaining their green leaf area over sustained periods. This study characterizes the leaf senescence process in sunflower through a systems biology approach integrating transcriptomic and metabolomic analyses: plants being grown under both glasshouse and field conditions. Our results revealed a correspondence between profile changes detected at the molecular, biochemical and physiological level throughout the progression of leaf senescence measured at different plant developmental stages. Early metabolic changes were detected prior to anthesis and before the onset of the first senescence symptoms, with more pronounced changes observed when physiological and molecular variables were assessed under field conditions. During leaf development, photosynthetic activity and cell growth processes decreased, whereas sucrose, fatty acid, nucleotide and amino acid metabolisms increased. Pathways related to nutrient recycling processes were also up-regulated. Members of the NAC, AP2-EREBP, HB, bZIP and MYB transcription factor families showed high expression levels, and their expression level was highly correlated, suggesting their involvement in sunflower senescence. The results of this study thus contribute to the elucidation of the molecular mechanisms involved in the onset and progression of leaf senescence in sunflower leaves as well as to the identification of candidate genes involved in this process. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26132509?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maroñas, Olalla</style></author><author><style face="normal" font="default" size="100%">Latorre, Ana</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Pirmohamed, Munir</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Antona, Cristina</style></author><author><style face="normal" font="default" size="100%">Siest, Gérard</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">LLerena, Adrián</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Progress in pharmacogenetics: consortiums and new strategies.</style></title><secondary-title><style face="normal" font="default" size="100%">Drug Metab Pers Ther</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Drug Metab Pers Ther</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cooperative Behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Screening Assays</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Patient Care Team</style></keyword><keyword><style  face="normal" font="default" size="100%">pharmacogenetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">17-23</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Pharmacogenetics (PGx), as a field dedicated to achieving the goal of personalized medicine (PM), is devoted to the study of genes involved in inter-individual response to drugs. Due to its nature, PGx requires access to large samples; therefore, in order to progress, the formation of collaborative consortia seems to be crucial. Some examples of this collective effort are the European Society of Pharmacogenomics and personalized Therapy and the Ibero-American network of Pharmacogenetics. As an emerging field, one of the major challenges that PGx faces is translating their discoveries from research bench to bedside. The development of genomic high-throughput technologies is generating a revolution and offers the possibility of producing vast amounts of genome-wide single nucleotide polymorphisms for each patient. Moreover, there is a need of identifying and replicating associations of new biomarkers, and, in addition, a greater effort must be invested in developing regulatory organizations to accomplish a correct standardization. In this review, we outline the current progress in PGx using examples to highlight both the importance of polymorphisms and the research strategies for their detection. These concepts need to be applied together with a proper dissemination of knowledge to improve clinician and patient understanding, in a multidisciplinary team-based approach. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26913460?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Urreizti, Roser</style></author><author><style face="normal" font="default" size="100%">Roca-Ayats, Neus</style></author><author><style face="normal" font="default" size="100%">Trepat, Judith</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Alemán, Alejandro</style></author><author><style face="normal" font="default" size="100%">Orteschi, Daniela</style></author><author><style face="normal" font="default" size="100%">Marangi, Giuseppe</style></author><author><style face="normal" font="default" size="100%">Neri, Giovanni</style></author><author><style face="normal" font="default" size="100%">Opitz, John M</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Cormand, Bru</style></author><author><style face="normal" font="default" size="100%">Vilageliu, Lluïsa</style></author><author><style face="normal" font="default" size="100%">Balcells, Susana</style></author><author><style face="normal" font="default" size="100%">Grinberg, Daniel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Screening of CD96 and ASXL1 in 11 patients with Opitz C or Bohring-Opitz syndromes.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Antigens, CD</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Craniosynostoses</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Intellectual Disability</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">170A</style></volume><pages><style face="normal" font="default" size="100%">24-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Opitz C trigonocephaly (or Opitz C syndrome, OTCS) and Bohring-Opitz syndrome (BOS or C-like syndrome) are two rare genetic disorders with phenotypic overlap. The genetic causes of these diseases are not understood. However, two genes have been associated with OTCS or BOS with dominantly inherited de novo mutations. Whereas CD96 has been related to OTCS (one case) and to BOS (one case), ASXL1 has been related to BOS only (several cases). In this study we analyze CD96 and ASXL1 in a group of 11 affected individuals, including 2 sibs, 10 of them were diagnosed with OTCS, and one had a BOS phenotype. Exome sequences were available on six patients with OTCS and three parent pairs. Thus, we could analyze the CD96 and ASXL1 sequences in these patients bioinformatically. Sanger sequencing of all exons of CD96 and ASXL1 was carried out in the remaining patients. Detailed scrutiny of the sequences and assessment of variants allowed us to exclude putative pathogenic and private mutations in all but one of the patients. In this patient (with BOS) we identified a de novo mutation in ASXL1 (c.2100dupT). By nature and location within the gene, this mutation resembles those previously described in other BOS patients and we conclude that it may be responsible for the condition. Our results indicate that in 10 of 11, the disease (OTCS or BOS) cannot be explained by small changes in CD96 or ASXL1. However, the cohort is too small to make generalizations about the genetic etiology of these diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26768331?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Razzoli, Maria</style></author><author><style face="normal" font="default" size="100%">Frontini, Andrea</style></author><author><style face="normal" font="default" size="100%">Gurney, Allison</style></author><author><style face="normal" font="default" size="100%">Mondini, Eleonora</style></author><author><style face="normal" font="default" size="100%">Cubuk, Cankut</style></author><author><style face="normal" font="default" size="100%">Katz, Liora S</style></author><author><style face="normal" font="default" size="100%">Cero, Cheryl</style></author><author><style face="normal" font="default" size="100%">Bolan, Patrick J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Vidal-Puig, Antonio</style></author><author><style face="normal" font="default" size="100%">Cinti, Saverio</style></author><author><style face="normal" font="default" size="100%">Bartolomucci, Alessandro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Stress-induced activation of brown adipose tissue prevents obesity in conditions of low adaptive thermogenesis.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Metab</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Metab</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">19-33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Stress-associated conditions such as psychoemotional reactivity and depression have been paradoxically linked to either weight gain or weight loss. This bi-directional effect of stress is not understood at the functional level. Here we tested the hypothesis that pre-stress level of adaptive thermogenesis and brown adipose tissue (BAT) functions explain the vulnerability or resilience to stress-induced obesity.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We used wt and triple β1,β2,β3-Adrenergic Receptors knockout (β-less) mice exposed to a model of chronic subordination stress (CSS) at either room temperature (22 °C) or murine thermoneutrality (30 °C). A combined behavioral, physiological, molecular, and immunohistochemical analysis was conducted to determine stress-induced modulation of energy balance and BAT structure and function. Immortalized brown adipocytes were used for in vitro assays.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Departing from our initial observation that βARs are dispensable for cold-induced BAT browning, we demonstrated that under physiological conditions promoting low adaptive thermogenesis and BAT activity (e.g. thermoneutrality or genetic deletion of the βARs), exposure to CSS acted as a stimulus for BAT activation and thermogenesis, resulting in resistance to diet-induced obesity despite the presence of hyperphagia. Conversely, in wt mice acclimatized to room temperature, and therefore characterized by sustained BAT function, exposure to CSS increased vulnerability to obesity. Exposure to CSS enhanced the sympathetic innervation of BAT in wt acclimatized to thermoneutrality and in β-less mice. Despite increased sympathetic innervation suggesting adrenergic-mediated browning, norepinephrine did not promote browning in βARs knockout brown adipocytes, which led us to identify an alternative sympathetic/brown adipocytes purinergic pathway in the BAT. This pathway is downregulated under conditions of low adaptive thermogenesis requirements, is induced by stress, and elicits activation of UCP1 in wt and β-less brown adipocytes. Importantly, this purinergic pathway is conserved in human BAT.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;Our findings demonstrate that thermogenesis and BAT function are determinant of the resilience or vulnerability to stress-induced obesity. Our data support a model in which adrenergic and purinergic pathways exert complementary/synergistic functions in BAT, thus suggesting an alternative to βARs agonists for the activation of human BAT.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26844204?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lucariello, Mario</style></author><author><style face="normal" font="default" size="100%">Vidal, Enrique</style></author><author><style face="normal" font="default" size="100%">Vidal, Silvia</style></author><author><style face="normal" font="default" size="100%">Saez, Mauricio</style></author><author><style face="normal" font="default" size="100%">Roa, Laura</style></author><author><style face="normal" font="default" size="100%">Huertas, Dori</style></author><author><style face="normal" font="default" size="100%">Pineda, Mercè</style></author><author><style face="normal" font="default" size="100%">Dalfó, Esther</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Jurado, Paola</style></author><author><style face="normal" font="default" size="100%">Armstrong, Judith</style></author><author><style face="normal" font="default" size="100%">Esteller, Manel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole exome sequencing of Rett syndrome-like patients reveals the mutational diversity of the clinical phenotype.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Caenorhabditis elegans</style></keyword><keyword><style  face="normal" font="default" size="100%">Carrier Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Cycle Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Forkhead Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Methyl-CpG-Binding Protein 2</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Nerve Tissue Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Serine-Threonine Kinases</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptors, Nicotinic</style></keyword><keyword><style  face="normal" font="default" size="100%">Rett Syndrome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">135</style></volume><pages><style face="normal" font="default" size="100%">1343-1354</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Classical Rett syndrome (RTT) is a neurodevelopmental disorder where most of cases carry MECP2 mutations. Atypical RTT variants involve mutations in CDKL5 and FOXG1. However, a subset of RTT patients remains that do not carry any mutation in the described genes. Whole exome sequencing was carried out in a cohort of 21 female probands with clinical features overlapping with those of RTT, but without mutations in the customarily studied genes. Candidates were functionally validated by assessing the appearance of a neurological phenotype in Caenorhabditis elegans upon disruption of the corresponding ortholog gene. We detected pathogenic variants that accounted for the RTT-like phenotype in 14 (66.6 %) patients. Five patients were carriers of mutations in genes already known to be associated with other syndromic neurodevelopmental disorders. We determined that the other patients harbored mutations in genes that have not previously been linked to RTT or other neurodevelopmental syndromes, such as the ankyrin repeat containing protein ANKRD31 or the neuronal acetylcholine receptor subunit alpha-5 (CHRNA5). Furthermore, worm assays demonstrated that mutations in the studied candidate genes caused locomotion defects. Our findings indicate that mutations in a variety of genes contribute to the development of RTT-like phenotypes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27541642?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Romero, Atocha</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">López-Perolio, Irene</style></author><author><style face="normal" font="default" size="100%">Ruiz de Garibay, Gorka</style></author><author><style face="normal" font="default" size="100%">García-Sáenz, José A</style></author><author><style face="normal" font="default" size="100%">Garre, Pilar</style></author><author><style face="normal" font="default" size="100%">Ayllón, Patricia</style></author><author><style face="normal" font="default" size="100%">Benito, Esperanza</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Díaz-Rubio, Eduardo</style></author><author><style face="normal" font="default" size="100%">Caldés, Trinidad</style></author><author><style face="normal" font="default" size="100%">de la Hoya, Miguel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BRCA1 Alternative splicing landscape in breast tissue samples.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC cancer</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.biomedcentral.com/1471-2407/15/219</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">219</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: BRCA1 is a key protein in cell network, involved in DNA repair pathways and cell cycle. Recently, the ENIGMA consortium has reported a high number of alternative splicing (AS) events at this locus in blood-derived samples. However, BRCA1 splicing pattern in breast tissue samples is unknown. Here, we provide an accurate description of BRCA1 splicing events distribution in breast tissue samples. METHODS: BRCA1 splicing events were scanned in 70 breast tumor samples, 4 breast samples from healthy individuals and in 72 blood-derived samples by capillary electrophoresis (capillary EP). Molecular subtype was identified in all tumor samples. Splicing events were considered predominant if their relative expression level was at least the 10% of the full-length reference signal. RESULTS: 54 BRCA1 AS events were identified, 27 of them were annotated as predominant in at least one sample. Δ5q, Δ13, Δ9, Δ5 and ▼1aA were significantly more frequently annotated as predominant in breast tumor samples than in blood-derived samples. Predominant splicing events were, on average, more frequent in tumor samples than in normal breast tissue samples (P = 0.010). Similarly, likely inactivating splicing events (PTC-NMDs, Non-Coding, Δ5 and Δ18) were more frequently annotated as predominant in tumor than in normal breast samples (P = 0.020), whereas there were no significant differences for other splicing events (No-Fs) frequency distribution between tumor and normal breast samples (P = 0.689). CONCLUSIONS: Our results complement recent findings by the ENIGMA consortium, demonstrating that BRCA1 AS, despite its tremendous complexity, is similar in breast and blood samples, with no evidences for tissue specific AS events. Further on, we conclude that somatic inactivation of BRCA1 through spliciogenic mutations is, at best, a rare mechanism in breast carcinogenesis, albeit our data detects an excess of likely inactivating AS events in breast tumor samples.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ewing, Adam D</style></author><author><style face="normal" font="default" size="100%">Houlahan, Kathleen E</style></author><author><style face="normal" font="default" size="100%">Hu, Yin</style></author><author><style face="normal" font="default" size="100%">Ellrott, Kyle</style></author><author><style face="normal" font="default" size="100%">Caloian, Cristian</style></author><author><style face="normal" font="default" size="100%">Yamaguchi, Takafumi N</style></author><author><style face="normal" font="default" size="100%">Bare, J Christopher</style></author><author><style face="normal" font="default" size="100%">P’ng, Christine</style></author><author><style face="normal" font="default" size="100%">Waggott, Daryl</style></author><author><style face="normal" font="default" size="100%">Sabelnykova, Veronica Y</style></author><author><style face="normal" font="default" size="100%">Kellen, Michael R</style></author><author><style face="normal" font="default" size="100%">Norman, Thea C</style></author><author><style face="normal" font="default" size="100%">Haussler, David</style></author><author><style face="normal" font="default" size="100%">Friend, Stephen H</style></author><author><style face="normal" font="default" size="100%">Stolovitzky, Gustavo</style></author><author><style face="normal" font="default" size="100%">Margolin, Adam A</style></author><author><style face="normal" font="default" size="100%">Stuart, Joshua M</style></author><author><style face="normal" font="default" size="100%">Boutros, Paul C</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">ICGC-TCGA DREAM Somatic Mutation Calling Challenge participants</style></author><author><style face="normal" font="default" size="100%">Liu Xi</style></author><author><style face="normal" font="default" size="100%">Ninad Dewal</style></author><author><style face="normal" font="default" size="100%">Yu Fan</style></author><author><style face="normal" font="default" size="100%">Wenyi Wang</style></author><author><style face="normal" font="default" size="100%">David Wheeler</style></author><author><style face="normal" font="default" size="100%">Andreas Wilm</style></author><author><style face="normal" font="default" size="100%">Grace Hui Ting</style></author><author><style face="normal" font="default" size="100%">Chenhao Li</style></author><author><style face="normal" font="default" size="100%">Denis Bertrand</style></author><author><style face="normal" font="default" size="100%">Niranjan Nagarajan</style></author><author><style face="normal" font="default" size="100%">Qing-Rong Chen</style></author><author><style face="normal" font="default" size="100%">Chih-Hao Hsu</style></author><author><style face="normal" font="default" size="100%">Ying Hu</style></author><author><style face="normal" font="default" size="100%">Chunhua Yan</style></author><author><style face="normal" font="default" size="100%">Warren Kibbe</style></author><author><style face="normal" font="default" size="100%">Daoud Meerzaman</style></author><author><style face="normal" font="default" size="100%">Kristian Cibulskis</style></author><author><style face="normal" font="default" size="100%">Mara Rosenberg</style></author><author><style face="normal" font="default" size="100%">Louis Bergelson</style></author><author><style face="normal" font="default" size="100%">Adam Kiezun</style></author><author><style face="normal" font="default" size="100%">Amie Radenbaugh</style></author><author><style face="normal" font="default" size="100%">Anne-Sophie Sertier</style></author><author><style face="normal" font="default" size="100%">Anthony Ferrari</style></author><author><style face="normal" font="default" size="100%">Laurie Tonton</style></author><author><style face="normal" font="default" size="100%">Kunal Bhutani</style></author><author><style face="normal" font="default" size="100%">Nancy F Hansen</style></author><author><style face="normal" font="default" size="100%">Difei Wang</style></author><author><style face="normal" font="default" size="100%">Lei Song</style></author><author><style face="normal" font="default" size="100%">Zhongwu Lai</style></author><author><style face="normal" font="default" size="100%">Liao, Yang</style></author><author><style face="normal" font="default" size="100%">Shi, Wei</style></author><author><style face="normal" font="default" size="100%">Carbonell-Caballero, José</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Cheryl C K Lau</style></author><author><style face="normal" font="default" size="100%">Justin Guinney</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature methods</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cancer</style></keyword><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">variant calling</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015 May 18</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3407.html</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alvarez-Mora, M I</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Revenga, L</style></author><author><style face="normal" font="default" size="100%">Madrigal, I</style></author><author><style face="normal" font="default" size="100%">García-García, F</style></author><author><style face="normal" font="default" size="100%">Duran, M</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Estivill, X</style></author><author><style face="normal" font="default" size="100%">Milà, M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deregulation of key signaling pathways involved in oocyte maturation in FMR1 premutation carriers with Fragile X-associated primary ovarian insufficiency.</style></title><secondary-title><style face="normal" font="default" size="100%">Gene</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Gene</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Fragile X Mental Retardation Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Fragile X Syndrome</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Developmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene ontology</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Heterozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Oocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Primary Ovarian Insufficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015 Oct 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">571</style></volume><pages><style face="normal" font="default" size="100%">52-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;FMR1 premutation female carriers are at risk for Fragile X-associated primary ovarian insufficiency (FXPOI). Insights from knock-in mouse model have recently demonstrated that FXPOI is due to an increased rate of follicle depletion or an impaired development of the growing follicles. Molecular mechanisms responsible for this reduced viability are still unknown. In an attempt to provide new data on the mechanisms that lead to FXPOI, we report the first investigation involving transcription profiling of total blood from FMR1 premutation female carriers with and without FXPOI. A total of 16 unrelated female individuals (6 FMR1 premutated females with FXPOI; 6 FMR1 premutated females without FXPOI; and 4 no-FXPOI females) were studied by whole human genome oligonucleotide microarray (Agilent Technologies). Fold change analysis did not show any genes with significant differential gene expression. However, functional profiling by gene set analysis showed large number of statistically significant deregulated GO annotations as well as numerous KEGG pathways in FXPOI females. These results suggest that the impairment of fertility in these females might be due to a generalized deregulation of key signaling pathways involved in oocyte maturation. In particular, the vasoendotelial growth factor signaling, the inositol phosphate metabolism, the cell cycle, and the MAPK signaling pathways were found to be down-regulated in FXPOI females. Furthermore, a high statistical enrichment of biological processes involved in cell death and survival were found deregulated among FXPOI females. Our results provide new strategic approaches to further investigate the molecular mechanisms and potential therapeutic targets for FXPOI not focused in a single gene but rather in the set of genes involved in these pathways. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26095811?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Sze-Man Tang, Clara</style></author><author><style face="normal" font="default" size="100%">Fernández, Raquel M.</style></author><author><style face="normal" font="default" size="100%">Sham, Pak-Chung</style></author><author><style face="normal" font="default" size="100%">Torroglosa, Ana</style></author><author><style face="normal" font="default" size="100%">Kwong-Hang Tam, Paul</style></author><author><style face="normal" font="default" size="100%">Espino-Paisán, Laura</style></author><author><style face="normal" font="default" size="100%">Cherny, Stacey S.</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Enguix-Riego, María Del Valle</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Garcia-Barceló, Maria-Mercè</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific Reports</style></secondary-title><short-title><style face="normal" font="default" size="100%">Sci Rep</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-12-2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/srep16473http://www.nature.com/articles/srep16473.pdfhttp://www.nature.com/articles/srep16473.pdfhttp://www.nature.com/articles/srep16473</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Sze-Man Tang, Clara</style></author><author><style face="normal" font="default" size="100%">Fernández, Raquel M</style></author><author><style face="normal" font="default" size="100%">Sham, Pak-Chung</style></author><author><style face="normal" font="default" size="100%">Torroglosa, Ana</style></author><author><style face="normal" font="default" size="100%">Kwong-Hang Tam, Paul</style></author><author><style face="normal" font="default" size="100%">Espino-Paisán, Laura</style></author><author><style face="normal" font="default" size="100%">Cherny, Stacey S</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Enguix-Riego, María Del Valle</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Garcia-Barceló, Maria-Mercè</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific reports</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">babelomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Hirschprung</style></keyword><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">prioritization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/articles/srep16473</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">16473</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Hirschsprung disease (HSCR; OMIM 142623) is a developmental disorder characterized by aganglionosis along variable lengths of the distal gastrointestinal tract, which results in intestinal obstruction. Interactions among known HSCR genes and/or unknown disease susceptibility loci lead to variable severity of phenotype. Neither linkage nor genome-wide association studies have efficiently contributed to completely dissect the genetic pathways underlying this complex genetic disorder. We have performed whole exome sequencing of 16 HSCR patients from 8 unrelated families with SOLID platform. Variants shared by affected relatives were validated by Sanger sequencing. We searched for genes recurrently mutated across families. Only variations in the FAT3 gene were significantly enriched in five families. Within-family analysis identified compound heterozygotes for AHNAK and several genes (N = 23) with heterozygous variants that co-segregated with the phenotype. Network and pathway analyses facilitated the discovery of polygenic inheritance involving FAT3, HSCR known genes and their gene partners. Altogether, our approach has facilitated the detection of more than one damaging variant in biologically plausible genes that could jointly contribute to the phenotype. Our data may contribute to the understanding of the complex interactions that occur during enteric nervous system development and the etiopathology of familial HSCR.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Navarro, Elena</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Martín-Sánchez, Marta</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Cristina Y.</style></author><author><style face="normal" font="default" size="100%">Fernández, Raquel M.</style></author><author><style face="normal" font="default" size="100%">Torroglosa, Ana</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Medical Genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1186/s12920-015-0160-7</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">83</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luzón-Toro, Berta</style></author><author><style face="normal" font="default" size="100%">Bleda, Marta</style></author><author><style face="normal" font="default" size="100%">Navarro, Elena</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Martín-Sánchez, Marta</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Cristina Y</style></author><author><style face="normal" font="default" size="100%">Fernández, Raquel M</style></author><author><style face="normal" font="default" size="100%">Torroglosa, Ana</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC medical genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">epistasis</style></keyword><keyword><style  face="normal" font="default" size="100%">GWAS</style></keyword><keyword><style  face="normal" font="default" size="100%">Thyroid cancer</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-015-0160-7</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">83</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk. METHODS: We carried out the first screening for epistasis by Multifactor-Dimensionality Reduction (MDR) in genome-wide association study (GWAS) on sMTC and juvenile PTC, to identify the potential simultaneous involvement of pairs of variants in the disease. RESULTS: We have identified two significant epistatic gene interactions in sMTC (CHFR-AC016582.2 and C8orf37-RNU1-55P) and three in juvenile PTC (RP11-648k4.2-DIO1, RP11-648k4.2-DMGDH and RP11-648k4.2-LOXL1). Interestingly, each interacting gene pair included a non-coding RNA, providing thus support to the relevance that these elements are increasingly gaining to explain carcinoma development and progression. CONCLUSIONS: Overall, this study contributes to the understanding of the genetic basis of thyroid carcinoma susceptibility in two different case scenarios such as sMTC and juvenile PTC.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Avila-Fernandez, Almudena</style></author><author><style face="normal" font="default" size="100%">Perez-Carro, Raquel</style></author><author><style face="normal" font="default" size="100%">Corton, Marta</style></author><author><style face="normal" font="default" size="100%">Lopez-Molina, Maria Isabel</style></author><author><style face="normal" font="default" size="100%">Campello, Laura</style></author><author><style face="normal" font="default" size="100%">Garanto, Alex</style></author><author><style face="normal" font="default" size="100%">Fernadez-Sanchez, Laura</style></author><author><style face="normal" font="default" size="100%">Duijkers, Lonneke</style></author><author><style face="normal" font="default" size="100%">Lopez-Martinez, Miguel Angel</style></author><author><style face="normal" font="default" size="100%">Riveiro-Alvarez, Rosa</style></author><author><style face="normal" font="default" size="100%">da Silva, Luciana Rodrigues Jacy</style></author><author><style face="normal" font="default" size="100%">Sanchez-Alcudia, Rocío</style></author><author><style face="normal" font="default" size="100%">Martin-Garrido, Esther</style></author><author><style face="normal" font="default" size="100%">Reyes, Noelia</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Sandoval, Blanca</style></author><author><style face="normal" font="default" size="100%">Collin, Rob W</style></author><author><style face="normal" font="default" size="100%">Cuenca, Nicolas</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole Exome Sequencing Reveals ZNF408 as a New Gene Associated With Autosomal Recessive Retinitis Pigmentosa with Vitreal Alterations.</style></title><secondary-title><style face="normal" font="default" size="100%">Human molecular genetics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015 Apr 16</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://hmg.oxfordjournals.org/content/early/2015/04/16/hmg.ddv140.abstract</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">14</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">4037-4048</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Retinitis Pigmentosa (RP) is a group of progressive inherited retinal dystrophies that cause visual impairment as a result of photoreceptor cell death. RP is heterogeneous, both clinically and genetically making difficult to establish precise genotype-phenotype correlations. In a Spanish family with autosomal recessive RP (arRP), homozygosity mapping and whole exome sequencing led to the identification of a homozygous mutation (c.358_359delGT; p.Ala122Leufs*2) in the ZNF408 gene. A screening performed in 217 additional unrelated families revealed another homozygous mutation (c.1621C&gt;T; p.Arg541Cys) in an isolated RP case. ZNF408 encodes a transcription factor that harbors ten predicted C2H2-type fingers thought to be implicated in DNA binding. To elucidate the ZNF408 role in the retina and the pathogenesis of these mutations we have performed different functional studies. By immunohistochemical analysis in healthy human retina, we identified that ZNF408 is expressed in both cone and rod photoreceptors, in a specific type of amacrine and ganglion cells, and in retinal blood vessels. ZNF408 revealed a cytoplasmic localization and a nuclear distribution in areas corresponding with the euchromatin fraction. Immunolocalization studies showed a partial mislocalization of the p.Arg541Cys mutant protein retaining part of the WT protein in the cytoplasm. Our study demonstrates that ZNF408, previously associated with Familial Exudative Vitreoretinopathy (FEVR), is a new gene causing arRP with vitreous condensations supporting the evidence that this protein plays additional functions into the human retina.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Avila-Fernandez, Almudena</style></author><author><style face="normal" font="default" size="100%">Perez-Carro, Raquel</style></author><author><style face="normal" font="default" size="100%">Corton, Marta</style></author><author><style face="normal" font="default" size="100%">Lopez-Molina, Maria Isabel</style></author><author><style face="normal" font="default" size="100%">Campello, Laura</style></author><author><style face="normal" font="default" size="100%">Garanto, Alejandro</style></author><author><style face="normal" font="default" size="100%">Fernandez-Sanchez, Laura</style></author><author><style face="normal" font="default" size="100%">Duijkers, Lonneke</style></author><author><style face="normal" font="default" size="100%">Lopez-Martinez, Miguel Angel</style></author><author><style face="normal" font="default" size="100%">Riveiro-Alvarez, Rosa</style></author><author><style face="normal" font="default" size="100%">da Silva, Luciana Rodrigues Jacy</style></author><author><style face="normal" font="default" size="100%">Sanchez-Alcudia, Rocío</style></author><author><style face="normal" font="default" size="100%">Martin-Garrido, Esther</style></author><author><style face="normal" font="default" size="100%">Reyes, Noelia</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Sandoval, Blanca</style></author><author><style face="normal" font="default" size="100%">Collin, Rob W J</style></author><author><style face="normal" font="default" size="100%">Cuenca, Nicolas</style></author><author><style face="normal" font="default" size="100%">Ayuso, Carmen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole-exome sequencing reveals ZNF408 as a new gene associated with autosomal recessive retinitis pigmentosa with vitreal alterations.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Chlorocebus aethiops</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">COS Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Homozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutant Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Retina</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Cone Photoreceptor Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinal Rod Photoreceptor Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Retinitis pigmentosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015 Jul 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">4037-48</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Retinitis pigmentosa (RP) is a group of progressive inherited retinal dystrophies that cause visual impairment as a result of photoreceptor cell death. RP is heterogeneous, both clinically and genetically making difficult to establish precise genotype-phenotype correlations. In a Spanish family with autosomal recessive RP (arRP), homozygosity mapping and whole-exome sequencing led to the identification of a homozygous mutation (c.358_359delGT; p.Ala122Leufs*2) in the ZNF408 gene. A screening performed in 217 additional unrelated families revealed another homozygous mutation (c.1621C&gt;T; p.Arg541Cys) in an isolated RP case. ZNF408 encodes a transcription factor that harbors 10 predicted C2H2-type fingers thought to be implicated in DNA binding. To elucidate the ZNF408 role in the retina and the pathogenesis of these mutations we have performed different functional studies. By immunohistochemical analysis in healthy human retina, we identified that ZNF408 is expressed in both cone and rod photoreceptors, in a specific type of amacrine and ganglion cells, and in retinal blood vessels. ZNF408 revealed a cytoplasmic localization and a nuclear distribution in areas corresponding with the euchromatin fraction. Immunolocalization studies showed a partial mislocalization of the p.Arg541Cys mutant protein retaining part of the WT protein in the cytoplasm. Our study demonstrates that ZNF408, previously associated with Familial Exudative Vitreoretinopathy (FEVR), is a new gene causing arRP with vitreous condensations supporting the evidence that this protein plays additional functions into the human retina. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">14</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/25882705?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Iglesias, Juan Manuel</style></author><author><style face="normal" font="default" size="100%">Leis, Olatz</style></author><author><style face="normal" font="default" size="100%">Pérez Ruiz, Estíbaliz</style></author><author><style face="normal" font="default" size="100%">Gumuzio Barrie, Juan</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Aduriz, Ariane</style></author><author><style face="normal" font="default" size="100%">Beloqui, Izaskun</style></author><author><style face="normal" font="default" size="100%">Hernandez-Garcia, Susana</style></author><author><style face="normal" font="default" size="100%">Lopez-Mato, Maria Paz</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Pandiella, Atanasio</style></author><author><style face="normal" font="default" size="100%">Menendez, Javier A</style></author><author><style face="normal" font="default" size="100%">Martin, Angel Garcia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Activation of the Sox2 RR2 Pluripotency Transcriptional Reporter in Human Breast Cancer Cell Lines is Dynamic and Labels Cells with Higher Tumorigenic Potential.</style></title><secondary-title><style face="normal" font="default" size="100%">Front Oncol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Front Oncol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">308</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The striking similarity displayed at the mechanistic level between tumorigenesis and the generation of induced pluripotent stem cells and the fact that genes and pathways relevant for embryonic development are reactivated during tumor progression highlights the link between pluripotency and cancer. Based on these observations, we tested whether it is possible to use a pluripotency-associated transcriptional reporter, whose activation is driven by the SRR2 enhancer from the Sox2 gene promoter (named S4+ reporter), to isolate cancer stem cells (CSCs) from breast cancer cell lines. The S4+ pluripotency transcriptional reporter allows the isolation of cells with enhanced tumorigenic potential and its activation was switched on and off in the cell lines studied, reflecting a plastic cellular process. Microarray analysis comparing the populations in which the reporter construct is active versus inactive showed that positive cells expressed higher mRNA levels of cytokines (IL-8, IL-6, TNF) and genes (such as ATF3, SNAI2, and KLF6) previously related with the CSC phenotype in breast cancer. &lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/25414831?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Bravo-Gil, Nereida</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Vázquez-Marouschek, Carmen</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet-Biedl family.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">124-33</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Bardet-Biedl syndrome (BBS) is a model ciliopathy characterized by a wide range of clinical variability. The heterogeneity of this condition is reflected in the number of underlying gene defects and the epistatic interactions between the proteins encoded. BBS is generally inherited in an autosomal recessive trait. However, in some families, mutations across different loci interact to modulate the expressivity of the phenotype. In order to investigate the magnitude of epistasis in one BBS family with remarkable intrafamilial phenotypic variability, we designed an exome sequencing-based approach using SOLID 5500xl platform. This strategy allowed the reliable detection of the primary causal mutations in our family consisting of two novel compound heterozygous mutations in McKusick-Kaufman syndrome (MKKS) gene (p.D90G and p.V396F). Additionally, exome sequencing enabled the detection of one novel heterozygous NPHP4 variant which is predicted to activate a cryptic acceptor splice site and is only present in the most severely affected patient. Here, we provide an exome sequencing analysis of a BBS family and show the potential utility of this tool, in combination with network analysis, to detect disease-causing mutations and second-site modifiers. Our data demonstrate how next-generation sequencing (NGS) can facilitate the dissection of epistatic phenomena, and shed light on the genetic basis of phenotypic variability. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24689075?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Vela-Boza, Alicia</style></author><author><style face="normal" font="default" size="100%">Nereida Bravo-Gil</style></author><author><style face="normal" font="default" size="100%">Antonio Rueda</style></author><author><style face="normal" font="default" size="100%">García-Alonso, Luz</style></author><author><style face="normal" font="default" size="100%">Vázquez-Marouschek, Carmen</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet–Biedl family</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Genetics &amp; Genomic Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://onlinelibrary.wiley.com/doi/10.1002/mgg3.50/full</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">124-133</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Bardet–Biedl syndrome (BBS) is a model ciliopathy characterized by a wide range of clinical variability. The heterogeneity of this condition is reflected in the number of underlying gene defects and the epistatic interactions between the proteins encoded. BBS is generally inherited in an autosomal recessive trait. However, in some families, mutations across different loci interact to modulate the expressivity of the phenotype. In order to investigate the magnitude of epistasis in one BBS family with remarkable intrafamilial phenotypic variability, we designed an exome sequencing–based approach using SOLID 5500xl platform. This strategy allowed the reliable detection of the primary causal mutations in our family consisting of two novel compound heterozygous mutations in McKusick–Kaufman syndrome (MKKS) gene (p.D90G and p.V396F). Additionally, exome sequencing enabled the detection of one novel heterozygous NPHP4 variant which is predicted to activate a cryptic acceptor splice site and is only present in the most severely affected patient. Here, we provide an exome sequencing analysis of a BBS family and show the potential utility of this tool, in combination with network analysis, to detect disease-causing mutations and second-site modifiers. Our data demonstrate how next-generation sequencing (NGS) can facilitate the dissection of epistatic phenomena, and shed light on the genetic basis of phenotypic variability.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tenorio, Jair</style></author><author><style face="normal" font="default" size="100%">Mansilla, Alicia</style></author><author><style face="normal" font="default" size="100%">Valencia, María</style></author><author><style face="normal" font="default" size="100%">Martínez-Glez, Víctor</style></author><author><style face="normal" font="default" size="100%">Romanelli, Valeria</style></author><author><style face="normal" font="default" size="100%">Arias, Pedro</style></author><author><style face="normal" font="default" size="100%">Castrejón, Nerea</style></author><author><style face="normal" font="default" size="100%">Poletta, Fernando</style></author><author><style face="normal" font="default" size="100%">Guillén-Navarro, Encarna</style></author><author><style face="normal" font="default" size="100%">Gordo, Gema</style></author><author><style face="normal" font="default" size="100%">Mansilla, Elena</style></author><author><style face="normal" font="default" size="100%">García-Santiago, Fé</style></author><author><style face="normal" font="default" size="100%">González-Casado, Isabel</style></author><author><style face="normal" font="default" size="100%">Vallespín, Elena</style></author><author><style face="normal" font="default" size="100%">Palomares, María</style></author><author><style face="normal" font="default" size="100%">Mori, María A</style></author><author><style face="normal" font="default" size="100%">Santos-Simarro, Fernando</style></author><author><style face="normal" font="default" size="100%">García-Miñaur, Sixto</style></author><author><style face="normal" font="default" size="100%">Fernández, Luis</style></author><author><style face="normal" font="default" size="100%">Mena, Rocío</style></author><author><style face="normal" font="default" size="100%">Benito-Sanz, Sara</style></author><author><style face="normal" font="default" size="100%">Del Pozo, Angela</style></author><author><style face="normal" font="default" size="100%">Silla, Juan Carlos</style></author><author><style face="normal" font="default" size="100%">Ibañez, Kristina</style></author><author><style face="normal" font="default" size="100%">López-Granados, Eduardo</style></author><author><style face="normal" font="default" size="100%">Martín-Trujillo, Alex</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Heath, Karen E</style></author><author><style face="normal" font="default" size="100%">Campos-Barros, Angel</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Nevado, Julián</style></author><author><style face="normal" font="default" size="100%">Monk, David</style></author><author><style face="normal" font="default" size="100%">Ruiz-Pérez, Víctor L</style></author><author><style face="normal" font="default" size="100%">Lapunzina, Pablo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A New Overgrowth Syndrome is Due to Mutations in RNF125.</style></title><secondary-title><style face="normal" font="default" size="100%">Human mutation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword><keyword><style  face="normal" font="default" size="100%">prioritization</style></keyword><keyword><style  face="normal" font="default" size="100%">Rare Disease</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Sep 5</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://onlinelibrary.wiley.com/doi/10.1002/humu.22689/abstract</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">1436–1441</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Overgrowth syndromes (OGS) are a group of disorders in which all parameters of growth and physical development are above the mean for age and sex. We evaluated a series of 270 families from the Spanish Overgrowth Syndrome Registry with no known overgrowth syndrome. We identified one de novo deletion and three missense mutations in RNF125 in six patients from 4 families with overgrowth, macrocephaly, intellectual disability, mild hydrocephaly, hypoglycaemia and inflammatory diseases resembling Sjögren syndrome. RNF125 encodes an E3 ubiquitin ligase and is a novel gene of OGS. Our studies of the RNF125 pathway point to upregulation of RIG-I-IPS1-MDA5 and/or disruption of the PI3K-AKT and interferon signaling pathways as the putative final effectors. This article is protected by copyright. All rights reserved.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">López-Domingo, Francisco J</style></author><author><style face="normal" font="default" size="100%">Florido, Javier P</style></author><author><style face="normal" font="default" size="100%">Rueda, Antonio</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Jun 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">1767-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;MOTIVATION: &lt;/b&gt;Targeted enrichment sequencing by next-generation sequencing is a common approach to interrogate specific loci or the whole exome in the human genome. The efficiency and the lack of bias in the enrichment process need to be assessed as a quality control step before performing downstream analysis of the sequence data. Tools that can report on the sensitivity, specificity, uniformity and other enrichment-specific features are needed.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We have implemented the next-generation sequencing data Capture Assessment Tool (ngsCAT), a tool that takes the information of the mapped reads and the coordinates of the targeted regions as input files, and generates a report with metrics and figures that allows the evaluation of the efficiency of the enrichment process. The tool can also take as input the information of two samples allowing the comparison of two different experiments.&lt;/p&gt;&lt;p&gt;&lt;b&gt;AVAILABILITY AND IMPLEMENTATION: &lt;/b&gt;Documentation and downloads for ngsCAT can be found at http://www.bioinfomgp.org/ngscat.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24578402?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gutiérrez, Jorge</style></author><author><style face="normal" font="default" size="100%">González-Pérez, Sergio</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Daly, Cara T</style></author><author><style face="normal" font="default" size="100%">Lorenzo, Oscar</style></author><author><style face="normal" font="default" size="100%">Revuelta, José L</style></author><author><style face="normal" font="default" size="100%">McCabe, Paul F</style></author><author><style face="normal" font="default" size="100%">Arellano, Juan B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Programmed cell death activated by Rose Bengal in Arabidopsis thaliana cell suspension cultures requires functional chloroplasts.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of experimental botany</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Apr 10</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://jxb.oxfordjournals.org/content/early/2014/04/09/jxb.eru151.long</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Light-grown Arabidopsis thaliana cell suspension culture (ACSC) were subjected to mild photooxidative damage with Rose Bengal (RB) with the aim of gaining a better understanding of singlet oxygen-mediated defence responses in plants. Additionally, ACSC were treated with H2O2 at concentrations that induced comparable levels of protein oxidation damage. Under low to medium light conditions, both RB and H2O2 treatments activated transcriptional defence responses and inhibited photosynthetic activity, but they differed in that programmed cell death (PCD) was only observed in cells treated with RB. When dark-grown ACSC were subjected to RB in the light, PCD was suppressed, indicating that the singlet oxygen-mediated signalling pathway in ACSC requires functional chloroplasts. Analysis of up-regulated transcripts in light-grown ACSC, treated with RB in the light, showed that both singlet oxygen-responsive transcripts and transcripts with a key role in hormone-activated PCD (i.e. ethylene and jasmonic acid) were present. A co-regulation analysis proved that ACSC treated with RB exhibited higher correlation with the conditional fluorescence (flu) mutant than with other singlet oxygen-producing mutants or wild-type plants subjected to high light. However, there was no evidence for the up-regulation of EDS1, suggesting that activation of PCD was not associated with the EXECUTER- and EDS1-dependent signalling pathway described in the flu mutant. Indigo Carmine and Methylene Violet, two photosensitizers unable to enter chloroplasts, did not activate transcriptional defence responses in ACSC; however, whether this was due to their location or to their inherently low singlet oxygen quantum efficiencies was not determined.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">García-Cazorla, Angels</style></author><author><style face="normal" font="default" size="100%">Oyarzabal, Alfonso</style></author><author><style face="normal" font="default" size="100%">Fort, Joana</style></author><author><style face="normal" font="default" size="100%">Robles, Concepción</style></author><author><style face="normal" font="default" size="100%">Castejón, Esperanza</style></author><author><style face="normal" font="default" size="100%">Ruiz-Sala, Pedro</style></author><author><style face="normal" font="default" size="100%">Bodoy, Susanna</style></author><author><style face="normal" font="default" size="100%">Merinero, Begoña</style></author><author><style face="normal" font="default" size="100%">Lopez-Sala, Anna</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Nunes, Virginia</style></author><author><style face="normal" font="default" size="100%">Ugarte, Magdalena</style></author><author><style face="normal" font="default" size="100%">Artuch, Rafael</style></author><author><style face="normal" font="default" size="100%">Palacín, Manuel</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Pombo, Pilar</style></author><author><style face="normal" font="default" size="100%">Alcaide, Patricia</style></author><author><style face="normal" font="default" size="100%">Navarrete, Rosa</style></author><author><style face="normal" font="default" size="100%">Sanz, Paloma</style></author><author><style face="normal" font="default" size="100%">Font-Llitjós, Mariona</style></author><author><style face="normal" font="default" size="100%">Vilaseca, Ma Antonia</style></author><author><style face="normal" font="default" size="100%">Ormaizabal, Aida</style></author><author><style face="normal" font="default" size="100%">Pristoupilova, Anna</style></author><author><style face="normal" font="default" size="100%">Agulló, Sergi Beltran</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Two novel mutations in the BCKDK (branched-chain keto-acid dehydrogenase kinase) gene are responsible for a neurobehavioral deficit in two pediatric unrelated patients.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acids, Branched-Chain</style></keyword><keyword><style  face="normal" font="default" size="100%">Developmental Disabilities</style></keyword><keyword><style  face="normal" font="default" size="100%">Fibroblasts</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Nervous System Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Pediatrics</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Kinases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">470-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Inactivating mutations in the BCKDK gene, which codes for the kinase responsible for the negative regulation of the branched-chain α-keto acid dehydrogenase complex (BCKD), have recently been associated with a form of autism in three families. In this work, two novel exonic BCKDK mutations, c.520C&gt;G/p.R174G and c.1166T&gt;C/p.L389P, were identified at the homozygous state in two unrelated children with persistently reduced body fluid levels of branched-chain amino acids (BCAAs), developmental delay, microcephaly, and neurobehavioral abnormalities. Functional analysis of the mutations confirmed the missense character of the c.1166T&gt;C change and showed a splicing defect r.[520c&gt;g;521_543del]/p.R174Gfs1*, for c.520C&gt;G due to the presence of a new donor splice site. Mutation p.L389P showed total loss of kinase activity. Moreover, patient-derived fibroblasts showed undetectable (p.R174Gfs1*) or barely detectable (p.L389P) levels of BCKDK protein and its phosphorylated substrate (phospho-E1α), resulting in increased BCKD activity and the very rapid BCAA catabolism manifested by the patients' clinical phenotype. Based on these results, a protein-rich diet plus oral BCAA supplementation was implemented in the patient homozygous for p.R174Gfs1*. This treatment normalized plasma BCAA levels and improved growth, developmental and behavioral variables. Our results demonstrate that BCKDK mutations can result in neurobehavioral deficits in humans and support the rationale for dietary intervention. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/24449431?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">García-Cazorla, Angels</style></author><author><style face="normal" font="default" size="100%">Oyarzabal, Alfonso</style></author><author><style face="normal" font="default" size="100%">Fort, Joana</style></author><author><style face="normal" font="default" size="100%">Robles, Concepción</style></author><author><style face="normal" font="default" size="100%">Castejón, Esperanza</style></author><author><style face="normal" font="default" size="100%">Ruiz-Sala, Pedro</style></author><author><style face="normal" font="default" size="100%">Bodoy, Susanna</style></author><author><style face="normal" font="default" size="100%">Merinero, Begoña</style></author><author><style face="normal" font="default" size="100%">Lopez-Sala, Anna</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Nunes, Virginia</style></author><author><style face="normal" font="default" size="100%">Ugarte, Magdalena</style></author><author><style face="normal" font="default" size="100%">Artuch, Rafael</style></author><author><style face="normal" font="default" size="100%">Palacín, Manuel</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Pombo, Pilar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Two Novel Mutations in the BCKDK Gene (Branched-Chain Keto-Acid Dehydrogenase Kinase) are Responsible of a Neurobehavioral Deficit in two Pediatric Unrelated Patients.</style></title><secondary-title><style face="normal" font="default" size="100%">Human mutation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Jan 21</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://onlinelibrary.wiley.com/doi/10.1002/humu.22513/abstract</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">470-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Inactivating mutations in the BCKDK gene, which codes for the kinase responsible for the negative regulation of the branched-chain keto-acid dehydrogenase complex (BCKD), have recently been associated with a form of autism in three families. In this work, two novel exonic BCKDK mutations, c.520C&gt;G/p.R174G and c.1166T&gt;C/p.L389P, were identified at the homozygous state in two unrelated children with persistently reduced body fluid levels of branched-chain amino acids (BCAAs), developmental delay, microcephaly and neurobehavioral abnormalities. Functional analysis of the mutations confirmed the missense character of the c.1166T&gt;C change and showed a splicing defect r.[520c&gt;g;521_543del]/p.R174Gfs1*, for c.520C&gt;G due to the presence of a new donor splice site. Mutation p.L389P showed total loss of kinase activity. Moreover, patient-derived fibroblasts showed undetectable (p.R174Gfs1*) or barely detectable (p.L389P) levels of BCKDK protein and its phosphorylated substrate (phospho-E1α), resulting in increased BCKD activity and the very rapid BCAA catabolism manifested by the patients’ clinical phenotype. Based on these results, a protein-rich diet plus oral BCAA supplementation was implemented in the patient homozygous for p.R174Gfs1*. This treatment normalized plasma BCAA levels and improved growth, developmental and behavioral variables. Our results demonstrate that BCKDK mutations can result in neurobehavioral deficits in humans and support the rationale for dietary intervention. This article is protected by copyright. All rights reserved.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Galan, Amparo</style></author><author><style face="normal" font="default" size="100%">Diaz-Gimeno, Patricia</style></author><author><style face="normal" font="default" size="100%">Poo, Maria Eugenia</style></author><author><style face="normal" font="default" size="100%">Valbuena, Diana</style></author><author><style face="normal" font="default" size="100%">Sanchez, Eva</style></author><author><style face="normal" font="default" size="100%">Ruiz, Veronica</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Conesa, Ana</style></author><author><style face="normal" font="default" size="100%">Simon, Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Defining the genomic signature of totipotency and pluripotency during early human development.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Blastocyst Inner Cell Mass</style></keyword><keyword><style  face="normal" font="default" size="100%">Blastomeres</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Embryonic Development</style></keyword><keyword><style  face="normal" font="default" size="100%">Embryonic Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Annotation</style></keyword><keyword><style  face="normal" font="default" size="100%">Pluripotent Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Totipotent Stem Cells</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e62135</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The genetic mechanisms governing human pre-implantation embryo development and the in vitro counterparts, human embryonic stem cells (hESCs), still remain incomplete. Previous global genome studies demonstrated that totipotent blastomeres from day-3 human embryos and pluripotent inner cell masses (ICMs) from blastocysts, display unique and differing transcriptomes. Nevertheless, comparative gene expression analysis has revealed that no significant differences exist between hESCs derived from blastomeres versus those obtained from ICMs, suggesting that pluripotent hESCs involve a new developmental progression. To understand early human stages evolution, we developed an undifferentiation network signature (UNS) and applied it to a differential gene expression profile between single blastomeres from day-3 embryos, ICMs and hESCs. This allowed us to establish a unique signature composed of highly interconnected genes characteristic of totipotency (61 genes), in vivo pluripotency (20 genes), and in vitro pluripotency (107 genes), and which are also proprietary according to functional analysis. This systems biology approach has led to an improved understanding of the molecular and signaling processes governing human pre-implantation embryo development, as well as enabling us to comprehend how hESCs might adapt to in vitro culture conditions.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/23614026?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tort, Frederic</style></author><author><style face="normal" font="default" size="100%">García-Silva, María Teresa</style></author><author><style face="normal" font="default" size="100%">Ferrer-Cortès, Xènia</style></author><author><style face="normal" font="default" size="100%">Navarro-Sastre, Aleix</style></author><author><style face="normal" font="default" size="100%">Garcia-Villoria, Judith</style></author><author><style face="normal" font="default" size="100%">Coll, Maria Josep</style></author><author><style face="normal" font="default" size="100%">Vidal, Enrique</style></author><author><style face="normal" font="default" size="100%">Jiménez-Almazán, Jorge</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Briones, Paz</style></author><author><style face="normal" font="default" size="100%">Elpeleg, Orly</style></author><author><style face="normal" font="default" size="100%">Ribes, Antonia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exome sequencing identifies a new mutation in SERAC1 in a patient with 3-methylglutaconic aciduria.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Genet Metab</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Genet Metab</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Carboxylic Ester Hydrolases</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolism, Inborn Errors</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013 Sep-Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">110</style></volume><pages><style face="normal" font="default" size="100%">73-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;3-Methylglutaconic aciduria (3-MGA-uria) is a heterogeneous group of syndromes characterized by an increased excretion of 3-methylglutaconic and 3-methylglutaric acids. Five types of 3-MGA-uria (I to V) with different clinical presentations have been described. Causative mutations in TAZ, OPA3, DNAJC19, ATP12, ATP5E, and TMEM70 have been identified. After excluding the known genetic causes of 3-MGA-uria we used exome sequencing to investigate a patient with Leigh syndrome and 3-MGA-uria. We identified a homozygous variant in SERAC1 (c.202C&gt;T; p.Arg68*), that generates a premature stop codon at position 68 of SERAC1 protein. Western blot analysis in patient's fibroblasts showed a complete absence of SERAC1 that was consistent with the prediction of a truncated protein and supports the pathogenic role of the mutation. During the course of this project a parallel study identified mutations in SERAC1 as the genetic cause of the disease in 15 patients with MEGDEL syndrome, which was compatible with the clinical and biochemical phenotypes of the patient described here. In addition, our patient developed microcephaly and optic atrophy, two features not previously reported in MEGDEL syndrome. We highlight the usefulness of exome sequencing to reveal the genetic bases of human rare diseases even if only one affected individual is available. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1-2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/23707711?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sánchez-Tena, Susana</style></author><author><style face="normal" font="default" size="100%">Reyes-Zurita, Fernando J</style></author><author><style face="normal" font="default" size="100%">Díaz-Moralli, Santiago</style></author><author><style face="normal" font="default" size="100%">Vinardell, Maria Pilar</style></author><author><style face="normal" font="default" size="100%">Reed, Michelle</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Lupiáñez, José A</style></author><author><style face="normal" font="default" size="100%">Günther, Ulrich</style></author><author><style face="normal" font="default" size="100%">Cascante, Marta</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Maslinic Acid-Enriched Diet Decreases Intestinal Tumorigenesis in Apc(Min/+) Mice through Transcriptomic and Metabolomic Reprogramming.</style></title><secondary-title><style face="normal" font="default" size="100%">PloS one</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e59392</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Chemoprevention is a pragmatic approach to reduce the risk of colorectal cancer, one of the leading causes of cancer-related death in western countries. In this regard, maslinic acid (MA), a pentacyclic triterpene extracted from wax-like coatings of olives, is known to inhibit proliferation and induce apoptosis in colon cancer cell lines without affecting normal intestinal cells. The present study evaluated the chemopreventive efficacy and associated mechanisms of maslinic acid treatment on spontaneous intestinal tumorigenesis in Apc(Min/+) mice. Twenty-two mice were randomized into 2 groups: control group and MA group, fed with a maslinic acid-supplemented diet for six weeks. MA treatment reduced total intestinal polyp formation by 45% (P&lt;0.01). Putative molecular mechanisms associated with suppressing intestinal polyposis in Apc(Min/+) mice were investigated by comparing microarray expression profiles of MA-treated and control mice and by analyzing the serum metabolic profile using NMR techniques. The different expression phenotype induced by MA suggested that it exerts its chemopreventive action mainly by inhibiting cell-survival signaling and inflammation. These changes eventually induce G1-phase cell cycle arrest and apoptosis. Moreover, the metabolic changes induced by MA treatment were associated with a protective profile against intestinal tumorigenesis. These results show the efficacy and underlying mechanisms of MA against intestinal tumor development in the Apc(Min/+) mice model, suggesting its chemopreventive potential against colorectal cancer.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Silbiger, Vivian N</style></author><author><style face="normal" font="default" size="100%">Luchessi, André D</style></author><author><style face="normal" font="default" size="100%">Hirata, Rosário D C</style></author><author><style face="normal" font="default" size="100%">Lima-Neto, Lídio G</style></author><author><style face="normal" font="default" size="100%">Cavichioli, Débora</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Brión, Maria</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dos Santos, Elizabete S</style></author><author><style face="normal" font="default" size="100%">Ramos, Rui F</style></author><author><style face="normal" font="default" size="100%">Sampaio, Marcelo F</style></author><author><style face="normal" font="default" size="100%">Armaganijan, Dikran</style></author><author><style face="normal" font="default" size="100%">Sousa, Amanda G M R</style></author><author><style face="normal" font="default" size="100%">Hirata, Mario H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Novel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome: Transcriptional profiling of acute coronary syndrome.</style></title><secondary-title><style face="normal" font="default" size="100%">Clinica chimica acta; international journal of clinical chemistry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013 Mar 24</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">{BACKGROUND: Genome-wide expression analysis using microarrays has been used as a research strategy to discovery new biomarkers and candidate genes for a number of diseases. We aim to find new biomarkers for the prediction of acute coronary syndrome (ACS) with a differentially expressed mRNA profiling approach using whole genomic expression analysis in a peripheral blood cell model from patients with early ACS. METHODS AND RESULTS: This study was carried out in two phases. On phase 1 a restricted clinical criteria (ACS-Ph1</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Silbiger, Vivian N</style></author><author><style face="normal" font="default" size="100%">Luchessi, André D</style></author><author><style face="normal" font="default" size="100%">Hirata, Rosário D C</style></author><author><style face="normal" font="default" size="100%">Lima-Neto, Lídio G</style></author><author><style face="normal" font="default" size="100%">Cavichioli, Débora</style></author><author><style face="normal" font="default" size="100%">Carracedo, Ángel</style></author><author><style face="normal" font="default" size="100%">Brión, Maria</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Dos Santos, Elizabete S</style></author><author><style face="normal" font="default" size="100%">Ramos, Rui F</style></author><author><style face="normal" font="default" size="100%">Sampaio, Marcelo F</style></author><author><style face="normal" font="default" size="100%">Armaganijan, Dikran</style></author><author><style face="normal" font="default" size="100%">Sousa, Amanda G M R</style></author><author><style face="normal" font="default" size="100%">Hirata, Mario H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Novel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome.</style></title><secondary-title><style face="normal" font="default" size="100%">Clin Chim Acta</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Clin Chim Acta</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acute Coronary Syndrome</style></keyword><keyword><style  face="normal" font="default" size="100%">Acute-Phase Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">biomarkers</style></keyword><keyword><style  face="normal" font="default" size="100%">Blood Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Early Diagnosis</style></keyword><keyword><style  face="normal" font="default" size="100%">gene expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013 Jun 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">421</style></volume><pages><style face="normal" font="default" size="100%">184-90</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Genome-wide expression analysis using microarrays has been used as a research strategy to discovery new biomarkers and candidate genes for a number of diseases. We aim to find new biomarkers for the prediction of acute coronary syndrome (ACS) with a differentially expressed mRNA profiling approach using whole genomic expression analysis in a peripheral blood cell model from patients with early ACS.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS AND RESULTS: &lt;/b&gt;This study was carried out in two phases. On phase 1 a restricted clinical criteria (ACS-Ph1, n=9 and CG-Ph1, n=6) was used in order to select potential mRNA biomarkers candidates. A subsequent phase 2 study was performed using selected phase 1 markers analyzed by RT-qPCR using a larger and independent casuistic (ACS-Ph2, n=74 and CG-Ph2, n=41). A total of 549 genes were found to be differentially expressed in the first 48 h after the ACS-Ph1. Technical and biological validation further confirmed that ALOX15, AREG, BCL2A1, BCL2L1, CA1, COX7B, ECHDC3, IL18R1, IRS2, KCNE1, MMP9, MYL4 and TREML4, are differentially expressed in both phases of this study.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Transcriptomic analysis by microarray technology demonstrated differential expression during a 48 h time course suggesting a potential use of some of these genes as biomarkers for very early stages of ACS, as well as for monitoring early cardiac ischemic recovery.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/23535507?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fernandez, Paula</style></author><author><style face="normal" font="default" size="100%">Soria, Marcelo</style></author><author><style face="normal" font="default" size="100%">Blesa, David</style></author><author><style face="normal" font="default" size="100%">Dirienzo, Julio</style></author><author><style face="normal" font="default" size="100%">Moschen, Sebastián</style></author><author><style face="normal" font="default" size="100%">Rivarola, Máximo</style></author><author><style face="normal" font="default" size="100%">Clavijo, Bernardo Jose</style></author><author><style face="normal" font="default" size="100%">Gonzalez, Sergio</style></author><author><style face="normal" font="default" size="100%">Peluffo, Lucila</style></author><author><style face="normal" font="default" size="100%">Príncipi, Dario</style></author><author><style face="normal" font="default" size="100%">Dosio, Guillermo</style></author><author><style face="normal" font="default" size="100%">Aguirrezabal, Luis</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Hopp, Esteban</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Heinz, Ruth Amelia</style></author><author><style face="normal" font="default" size="100%">Paniego, Norma</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray.</style></title><secondary-title><style face="normal" font="default" size="100%">PloS one</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0045899</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e45899</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (&gt;130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p&lt;0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Conesa-Zamora, Pablo</style></author><author><style face="normal" font="default" size="100%">García-Solano, José</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Del Carmen Turpin, María</style></author><author><style face="normal" font="default" size="100%">Trujillo-Santos, Javier</style></author><author><style face="normal" font="default" size="100%">Torres-Moreno, Daniel</style></author><author><style face="normal" font="default" size="100%">Oviedo-Ramírez, Isabel</style></author><author><style face="normal" font="default" size="100%">Carbonell-Muñoz, Rosa</style></author><author><style face="normal" font="default" size="100%">Muñoz-Delgado, Encarnación</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Braun, Edith</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Pérez-Guillermo, Miguel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expression profiling shows differential molecular pathways and provides potential new diagnostic biomarkers for colorectal serrated adenocarcinoma.</style></title><secondary-title><style face="normal" font="default" size="100%">International journal of cancer. Journal international du cancer</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Jun 14</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Serrated adenocarcinoma (SAC) is a recently recognized colorectal cancer (CRC) subtype accounting for 7.5-8.7% of CRCs. It has been shown that SAC has a poorer prognosis and has different molecular and immunohistochemical features compared to conventional carcinoma (CC) but, to date, only one previous study has analysed its mRNA expression profile by microarray. Using a different microarray platform, we have studied the molecular signature of 11 SACs and compared it with that of 15 matched CC with the aim of discerning the functions which characterize SAC biology and validating, at the mRNA and protein level, the most differentially expressed genes which were also tested using a validation set of 70 SACs and 70 CCs to assess their diagnostic and prognostic values. Microarray data showed a higher representation of morphogenesis-, hypoxia-, cytoskeleton- and vesicle transport-related functions and also an over-expression of fascin1 (actin-bundling protein associated with invasion) and the antiapoptotic gene hippocalcin in SAC all of which were validated both by qPCR and immunohistochemistry. Fascin1 expression was statistically associated with KRAS mutation with 88.6% sensitivity and 85.7% specificity for SAC diagnosis and the positivity of fascin1 or hippocalcin was highly suggestive of SAC diagnosis (sensitivity=100%). Evaluation of these markers in CRCs showing histological and molecular characteristics of high-level microsatellite instability (MSI-H) also helped to distinguish SACs from MSI-H CRCs. Molecular profiling demonstrates that SAC shows activation of distinct signalling pathways and that immunohistochemical fascin1 and hippocalcin expression can be reliably used for its differentiation from other CRC subtypes. © 2012 Wiley Periodicals, Inc.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carrero, Rubén</style></author><author><style face="normal" font="default" size="100%">Cerrada, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Lledó, Elisa</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Rubio, Mari-Paz</style></author><author><style face="normal" font="default" size="100%">Trigueros, César</style></author><author><style face="normal" font="default" size="100%">Dorronsoro, Akaitz</style></author><author><style face="normal" font="default" size="100%">Ruiz-Sauri, Amparo</style></author><author><style face="normal" font="default" size="100%">Montero, José Anastasio</style></author><author><style face="normal" font="default" size="100%">Sepúlveda, Pilar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IL1β induces mesenchymal stem cells migration and leucocyte chemotaxis through NF-κB.</style></title><secondary-title><style face="normal" font="default" size="100%">Stem Cell Rev Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stem Cell Rev Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cell Adhesion</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Movement</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Proliferation</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemokines</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemotaxis, Leukocyte</style></keyword><keyword><style  face="normal" font="default" size="100%">Collagen</style></keyword><keyword><style  face="normal" font="default" size="100%">Fibronectins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockdown Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">HEK293 Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">I-kappa B Kinase</style></keyword><keyword><style  face="normal" font="default" size="100%">Inflammation Mediators</style></keyword><keyword><style  face="normal" font="default" size="100%">Intercellular Signaling Peptides and Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Interleukin-1beta</style></keyword><keyword><style  face="normal" font="default" size="100%">Laminin</style></keyword><keyword><style  face="normal" font="default" size="100%">Leukocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Mesenchymal Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">NF-kappa B</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA Interference</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Sep</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">905-16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Mesenchymal stem cells are often transplanted into inflammatory environments where they are able to survive and modulate host immune responses through a poorly understood mechanism. In this paper we analyzed the responses of MSC to IL-1β: a representative inflammatory mediator. Microarray analysis of MSC treated with IL-1β revealed that this cytokine activateds a set of genes related to biological processes such as cell survival, cell migration, cell adhesion, chemokine production, induction of angiogenesis and modulation of the immune response. Further more detailed analysis by real-time PCR and functional assays revealed that IL-1β mainly increaseds the production of chemokines such as CCL5, CCL20, CXCL1, CXCL3, CXCL5, CXCL6, CXCL10, CXCL11 and CX(3)CL1, interleukins IL-6, IL-8, IL23A, IL32, Toll-like receptors TLR2, TLR4, CLDN1, metalloproteins MMP1 and MMP3, growth factors CSF2 and TNF-α, together with adhesion molecules ICAM1 and ICAM4. Functional analysis of MSC proliferation, migration and adhesion to extracellular matrix components revealed that IL-1β did not affect proliferation but also served to induce the secretion of trophic factors and adhesion to ECM components such as collagen and laminin. IL-1β treatment enhanced the ability of MSC to recruit monocytes and granulocytes in vitro. Blockade of NF-κβ transcription factor activation with IκB kinase beta (IKKβ) shRNA impaired MSC migration, adhesion and leucocyte recruitment, induced by IL-1β demonstrating that NF-κB pathway is an important downstream regulator of these responses. These findings are relevant to understanding the biological responses of MSC to inflammatory environments.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22467443?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Carbonell, José</style></author><author><style face="normal" font="default" size="100%">Alloza, Eva</style></author><author><style face="normal" font="default" size="100%">Arce, Pablo</style></author><author><style face="normal" font="default" size="100%">Borrego, Salud</style></author><author><style face="normal" font="default" size="100%">Santoyo, Javier</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ferrer, Macarena</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Jiménez-Almazán, Jorge</style></author><author><style face="normal" font="default" size="100%">Méndez-Vidal, Cristina</style></author><author><style face="normal" font="default" size="100%">González-del Pozo, María</style></author><author><style face="normal" font="default" size="100%">Vela, Alicia</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Shomi S</style></author><author><style face="normal" font="default" size="100%">Antiňolo, Guillermo</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A map of human microRNA variation uncovers unexpectedly high levels of variability.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome medicine</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Aug 20</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://genomemedicine.com/content/4/8/62/abstract</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">62</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are key components of the gene regulatory network in many species. During the past few years, these regulatory elements have been shown to be involved in an increasing number and range of diseases. Consequently, the compilation of a comprehensive map of natural variability in healthy population seems an obvious requirement for future research on miRNA-related pathologies. METHODS: Data on 14 populations from the 1000 Genomes Project were analysed, along with new data extracted from 60 exomes of healthy individuals from a southern Spain population, sequenced in the context of the Medical Genome Project, to derive an accurate map of miRNA variability. RESULTS: Despite the common belief that miRNAs are highly conserved elements, analysis of the sequences of the 1,152 individuals indicated that the observed level of variability is double what was expected. A total of 527 variants were found. Among these, 45 variants affected the recognition region of the corresponding miRNA and were found in 43 different miRNAs, 26 of which are known to be involved in 57 diseases. Different parts of the mature structure of the miRNA were affected to different degrees by variants, which suggests the existence of a selective pressure related to the relative functional impact of the change. Moreover, 41 variants showed a significant deviation from the Hardy-Weinberg equilibrium, which supports the existence of a selective process against some alleles. The average number of variants per individual in miRNAs was 28. CONCLUSIONS: Despite an expectation that miRNAs would be highly conserved genomic elements, our study reports a level of variability comparable to that observed for coding genes.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rizza, Serena</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Juarez, José</style></author><author><style face="normal" font="default" size="100%">Catara, Antonino</style></author><author><style face="normal" font="default" size="100%">Navarro, Luis</style></author><author><style face="normal" font="default" size="100%">Duran-Vila, Nuria</style></author><author><style face="normal" font="default" size="100%">Ancillo, Gema</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Microarray analysis of Etrog citron (Citrus medica L.) reveals changes in chloroplast, cell wall, peroxidase and symporter activities in response to viroid infection.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular plant pathology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Mar 15</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Viroids are small (246-401 nucleotides), single-stranded, circular RNA molecules that infect several crop plants and can cause diseases of economic importance. Citrus are the hosts in which the largest number of viroids have been identified. Citrus exocortis viroid (CEVd), the causal agent of citrus exocortis disease, induces considerable losses in citrus crops. Changes in the gene expression profile during the early (pre-symptomatic) and late (post-symptomatic) stages of Etrog citron infected with CEVd were investigated using a citrus cDNA microarray. MaSigPro analysis was performed and, on the basis of gene expression profiles as a function of the time after infection, the differentially expressed genes were classified into five clusters. FatiScan analysis revealed significant enrichment of functional categories for each cluster, indicating that viroid infection triggers important changes in chloroplast, cell wall, peroxidase and symporter activities.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">De Baets, Greet</style></author><author><style face="normal" font="default" size="100%">Van Durme, Joost</style></author><author><style face="normal" font="default" size="100%">Reumers, Joke</style></author><author><style face="normal" font="default" size="100%">Maurer-Stroh, Sebastian</style></author><author><style face="normal" font="default" size="100%">Vanhee, Peter</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, Joost</style></author><author><style face="normal" font="default" size="100%">Rousseau, Frederic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Meta-Analysis as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">D935-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Database issue</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22075996?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Götz, Stefan</style></author><author><style face="normal" font="default" size="100%">Arnold, Roland</style></author><author><style face="normal" font="default" size="100%">Sebastián-Leon, Patricia</style></author><author><style face="normal" font="default" size="100%">Martín-Rodríguez, Samuel</style></author><author><style face="normal" font="default" size="100%">Tischler, Patrick</style></author><author><style face="normal" font="default" size="100%">Jehl, Marc-André</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Rattei, Thomas</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">B2G-FAR, a species centered GO annotation repository.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics (Oxford, England)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Feb 18</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">919-924</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;MOTIVATION: Functional genomics research has expanded enormously in the last decade thanks to the cost-reduction in high-throughput technologies and the development of computational tools that generate, standardize and share information on gene and protein function such as the Gene Ontology (GO). Nevertheless many biologists, especially working with non-model organisms, still suffer from non-existing or low coverage functional annotation, or simply struggle retrieving, summarizing and querying these data. RESULTS: The Blast2GO Functional Annotation Repository (B2G-FAR) is a bioinformatics resource envisaged to provide functional information for otherwise uncharacterized sequence-data and offers data-mining tools to analyze a larger repertoire of species than currently available. This new annotation resource has been created by applying the Blast2GO functional annotation engine in a strongly high-throughput manner to the entire space of public available sequences. The resulting repository contains GO term predictions for over 13.2 million non-redundant protein sequences based on BLAST search alignments from the SIMAP database. We generated GO annotation for approximately 150.000 different taxa making available the 2000 species with the highest coverage through B2G-FAR. A second section within B2G-FAR holds functional annotations for 17 non-model organism Affymetrix GeneChips. Conclusions: B2G-FAR provides easy access to exhaustive functional annotation for 2000 species offering a good balance between quality and quantity, thereby supporting functional genomics research especially in the case of non-model organisms. AVAILABILITY: The annotation resource is available at http://b2gfar.bioinfo.cipf.es. CONTACT: aconesa@cipf.es, sgoetz@cipf.es.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prieur, Xavier</style></author><author><style face="normal" font="default" size="100%">Mok, Crystal Y L</style></author><author><style face="normal" font="default" size="100%">Velagapudi, Vidya R</style></author><author><style face="normal" font="default" size="100%">Núñez, Vanessa</style></author><author><style face="normal" font="default" size="100%">Fuentes, Lucía</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Ishikawa, Ko</style></author><author><style face="normal" font="default" size="100%">Camacho, Alberto</style></author><author><style face="normal" font="default" size="100%">Barbarroja, Nuria</style></author><author><style face="normal" font="default" size="100%">O’Rahilly, Stephen</style></author><author><style face="normal" font="default" size="100%">Sethi, Jaswinder</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Oresic, Matej</style></author><author><style face="normal" font="default" size="100%">Ricote, Mercedes</style></author><author><style face="normal" font="default" size="100%">Vidal-Puig, Antonio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential Lipid Partitioning Between Adipocytes and Tissue Macrophages Modulates Macrophage Lipotoxicity and M2/M1 Polarization in Obese Mice.</style></title><secondary-title><style face="normal" font="default" size="100%">Diabetes</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jan 24</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">60</style></volume><pages><style face="normal" font="default" size="100%">797-809</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;OBJECTIVE Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. RESEARCH DESIGN AND METHODS We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. RESULTS We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell-like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. CONCLUSIONS Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vivas, Yurena</style></author><author><style face="normal" font="default" size="100%">Martinez-Garcia, Cristina</style></author><author><style face="normal" font="default" size="100%">Izquierdo, Adriana</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Callejas, Sergio</style></author><author><style face="normal" font="default" size="100%">Velasco, Ismael</style></author><author><style face="normal" font="default" size="100%">Campbell, Mark</style></author><author><style face="normal" font="default" size="100%">Ros, Manuel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Ana</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Vidal-Puig, Antonio</style></author><author><style face="normal" font="default" size="100%">Medina-Gomez, Gema</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Early peroxisome proliferator-activated receptor gamma regulated genes involved in expansion of pancreatic beta cell mass.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Med Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Med Genomics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Proliferation</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Survival</style></keyword><keyword><style  face="normal" font="default" size="100%">Cholesterol</style></keyword><keyword><style  face="normal" font="default" size="100%">Down-Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockout Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Insulin Resistance</style></keyword><keyword><style  face="normal" font="default" size="100%">Insulin-Secreting Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidation-Reduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Phosphorylation</style></keyword><keyword><style  face="normal" font="default" size="100%">PPAR gamma</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Transforming Growth Factor beta</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Dec 30</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">86</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;The progression towards type 2 diabetes depends on the allostatic response of pancreatic beta cells to synthesise and secrete enough insulin to compensate for insulin resistance. The endocrine pancreas is a plastic tissue able to expand or regress in response to the requirements imposed by physiological and pathophysiological states associated to insulin resistance such as pregnancy, obesity or ageing, but the mechanisms mediating beta cell mass expansion in these scenarios are not well defined. We have recently shown that ob/ob mice with genetic ablation of PPARγ2, a mouse model known as the POKO mouse failed to expand its beta cell mass. This phenotype contrasted with the appropriate expansion of the beta cell mass observed in their obese littermate ob/ob mice. Thus, comparison of these models islets particularly at early ages could provide some new insights on early PPARγ dependent transcriptional responses involved in the process of beta cell mass expansion&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Here we have investigated PPARγ dependent transcriptional responses occurring during the early stages of beta cell adaptation to insulin resistance in wild type, ob/ob, PPARγ2 KO and POKO mice. We have identified genes known to regulate both the rate of proliferation and the survival signals of beta cells. Moreover we have also identified new pathways induced in ob/ob islets that remained unchanged in POKO islets, suggesting an important role for PPARγ in maintenance/activation of mechanisms essential for the continued function of the beta cell.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our data suggest that the expansion of beta cell mass observed in ob/ob islets is associated with the activation of an immune response that fails to occur in POKO islets. We have also indentified other PPARγ dependent differentially regulated pathways including cholesterol biosynthesis, apoptosis through TGF-β signaling and decreased oxidative phosphorylation.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/22208362?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-Pérez, Sergio</style></author><author><style face="normal" font="default" size="100%">Gutiérrez, Jorge</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Osuna, Daniel</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Lorenzo, Oscar</style></author><author><style face="normal" font="default" size="100%">Revuelta, José L</style></author><author><style face="normal" font="default" size="100%">Arellano, Juan B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Early transcriptional defence responses in Arabidopsis cell suspension culture under high light conditions.</style></title><secondary-title><style face="normal" font="default" size="100%">Plant physiology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Apr 29</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plantphysiol.org/content/early/2011/04/29/pp.111.177766.short?keytype=ref&amp;ijkey=ph5B6J2khjnqwzN</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">156</style></volume><pages><style face="normal" font="default" size="100%">1439-56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The early transcriptional defence responses and ROS production in Arabidopsis cell suspension culture (ACSC), containing functional chloroplasts, were examined at high light (HL). The transcriptional analysis revealed that most of the ROS markers identified among the 449 transcripts with significant differential expression were transcripts specifically up-regulated by singlet oxygen (1O2). On the contrary, minimal correlation was established with transcripts specifically up-regulated by superoxide radical (O2&amp;bull;) or hydrogen peroxide (H2O2). The transcriptional analysis was supported by fluorescence microscopy experiments. The incubation of ACSC with the 1O2 sensor green reagent and 2’,7’-dichlorofluorescein diacetate showed that the 30-min-HL-treated cultures emitted fluorescence that corresponded with the production of 1O2, but not of H2O2. Furthermore, the in vivo photodamage of the D1 protein of photosystem II (PSII) indicated that the photogeneration of 1O2 took place within the PSII reaction centre. Functional enrichment analyses identified transcripts that are key components of the ROS signalling transduction pathway in plants as well as others encoding transcription factors that regulate both ROS scavenging and water deficit stress. A meta-analysis examining the transcriptional profiles of mutants and hormone treatments in Arabidopsis showed a high correlation between ACSC at HL and the flu mutant family of Arabidopsis, a producer of 1O2 in plastids. Intriguingly, a high correlation was also observed with aba1 and max4, two mutants with defects in the biosynthesis pathways of two key (apo)carotenoid-derived plant hormones (i.e. ABA and strigolactones, respectively). ACSC has proven to be a valuable system for studying early transcriptional responses to HL stress.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">González-Pérez, Sergio</style></author><author><style face="normal" font="default" size="100%">Gutiérrez, Jorge</style></author><author><style face="normal" font="default" size="100%">Garcia-Garcia, Francisco</style></author><author><style face="normal" font="default" size="100%">Osuna, Daniel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Lorenzo, Oscar</style></author><author><style face="normal" font="default" size="100%">Revuelta, José L</style></author><author><style face="normal" font="default" size="100%">Arellano, Juan B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Early transcriptional defense responses in Arabidopsis cell suspension culture under high-light conditions.</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Physiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Plant Physiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Arabidopsis</style></keyword><keyword><style  face="normal" font="default" size="100%">Blotting, Western</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Culture Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Cells, Cultured</style></keyword><keyword><style  face="normal" font="default" size="100%">Chloroplasts</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrogen Peroxide</style></keyword><keyword><style  face="normal" font="default" size="100%">Light</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Photosystem II Protein Complex</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Growth Regulators</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Reverse Transcriptase Polymerase Chain Reaction</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Stress, Physiological</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">156</style></volume><pages><style face="normal" font="default" size="100%">1439-56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The early transcriptional defense responses and reactive oxygen species (ROS) production in Arabidopsis (Arabidopsis thaliana) cell suspension culture (ACSC), containing functional chloroplasts, were examined at high light (HL). The transcriptional analysis revealed that most of the ROS markers identified among the 449 transcripts with significant differential expression were transcripts specifically up-regulated by singlet oxygen ((1)O(2)). On the contrary, minimal correlation was established with transcripts specifically up-regulated by superoxide radical or hydrogen peroxide. The transcriptional analysis was supported by fluorescence microscopy experiments. The incubation of ACSC with the (1)O(2) sensor green reagent and 2',7'-dichlorofluorescein diacetate showed that the 30-min-HL-treated cultures emitted fluorescence that corresponded with the production of (1)O(2) but not of hydrogen peroxide. Furthermore, the in vivo photodamage of the D1 protein of photosystem II indicated that the photogeneration of (1)O(2) took place within the photosystem II reaction center. Functional enrichment analyses identified transcripts that are key components of the ROS signaling transduction pathway in plants as well as others encoding transcription factors that regulate both ROS scavenging and water deficit stress. A meta-analysis examining the transcriptional profiles of mutants and hormone treatments in Arabidopsis showed a high correlation between ACSC at HL and the fluorescent mutant family of Arabidopsis, a producer of (1)O(2) in plastids. Intriguingly, a high correlation was also observed with ABA deficient1 and more axillary growth4, two mutants with defects in the biosynthesis pathways of two key (apo)carotenoid-derived plant hormones (i.e. abscisic acid and strigolactones, respectively). ACSC has proven to be a valuable system for studying early transcriptional responses to HL stress.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21531897?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">De Baets, Greet</style></author><author><style face="normal" font="default" size="100%">Reumers, Joke</style></author><author><style face="normal" font="default" size="100%">Delgado Blanco, Javier</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, Joost</style></author><author><style face="normal" font="default" size="100%">Rousseau, Frederic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An evolutionary trade-off between protein turnover rate and protein aggregation favors a higher aggregation propensity in fast degrading proteins.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS computational biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e1002090</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We previously showed the existence of selective pressure against protein aggregation by the enrichment of aggregation-opposing ’gatekeeper’ residues at strategic places along the sequence of proteins. Here we analyzed the relationship between protein lifetime and protein aggregation by combining experimentally determined turnover rates, expression data, structural data and chaperone interaction data on a set of more than 500 proteins. We find that selective pressure on protein sequences against aggregation is not homogeneous but that short-living proteins on average have a higher aggregation propensity and fewer chaperone interactions than long-living proteins. We also find that short-living proteins are more often associated to deposition diseases. These findings suggest that the efficient degradation of high-turnover proteins is sufficient to preclude aggregation, but also that factors that inhibit proteasomal activity, such as physiological ageing, will primarily affect the aggregation of short-living proteins.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Leida, Carmen</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Llácer, Gerardo</style></author><author><style face="normal" font="default" size="100%">Badenes, María Luisa</style></author><author><style face="normal" font="default" size="100%">Ríos, Gabino</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Histone modifications and expression of DAM6 gene in peach are modulated during bud dormancy release in a cultivar-dependent manner.</style></title><secondary-title><style face="normal" font="default" size="100%">The New phytologist</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Sep 7</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&amp;bull; Bud dormancy release in many woody perennial plants responds to the seasonal accumulation of chilling stimulus. MADS-box transcription factors encoded by DORMANCY ASSOCIATED MADS-box (DAM) genes in peach (Prunus persica) are implicated in this pathway, but other regulatory factors remain to be identified. In addition, the regulation of DAM gene expression is not well known at the molecular level. &amp;bull; A microarray hybridization approach was performed to identify genes whose expression correlates with the bud dormancy-related behaviour in 10 different peach cultivars. Histone modifications in DAM6 gene were investigated by chromatin immunoprecipitation in two different cultivars. &amp;bull; The expression of DAM4-DAM6 and several genes related to abscisic acid and drought stress response correlated with the dormancy behaviour of peach cultivars. The trimethylation of histone H3 at K27 in the DAM6 promoter, coding region and the second large intron was preceded by a decrease in acetylated H3 and trimethylated H3K4 in the region of translation start, coinciding with repression of DAM6 during dormancy release. &amp;bull; Analysis of chromatin modifications reinforced the role of epigenetic mechanisms in DAM6 regulation and bud dormancy release, and highlighted common features with the vernalization process in Arabidopsis thaliana and cereals.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yung, Sun</style></author><author><style face="normal" font="default" size="100%">Ledran, Maria</style></author><author><style face="normal" font="default" size="100%">Moreno-Gimeno, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Conesa, Ana</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dimmick, Ian</style></author><author><style face="normal" font="default" size="100%">Slater, Nicholas J</style></author><author><style face="normal" font="default" size="100%">Marenah, Lamin</style></author><author><style face="normal" font="default" size="100%">Real, Pedro J</style></author><author><style face="normal" font="default" size="100%">Paraskevopoulou, Iliana</style></author><author><style face="normal" font="default" size="100%">Bisbal, Viviana</style></author><author><style face="normal" font="default" size="100%">Burks, Deborah</style></author><author><style face="normal" font="default" size="100%">Santibanez-Koref, Mauro</style></author><author><style face="normal" font="default" size="100%">Moreno, Ruben</style></author><author><style face="normal" font="default" size="100%">Mountford, Joanne</style></author><author><style face="normal" font="default" size="100%">Menendez, Pablo</style></author><author><style face="normal" font="default" size="100%">Armstrong, Lyle</style></author><author><style face="normal" font="default" size="100%">Lako, Majlinda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mol Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acute Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Anemia, Hemolytic</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Basic Helix-Loop-Helix Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Line</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Lineage</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Embryonic Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Erythroid Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Flow Cytometry</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Hematopoietic Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Myeloid Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Paracrine Communication</style></keyword><keyword><style  face="normal" font="default" size="100%">Proto-Oncogene Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Reverse Transcriptase Polymerase Chain Reaction</style></keyword><keyword><style  face="normal" font="default" size="100%">rho GTP-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Stem Cell Transplantation</style></keyword><keyword><style  face="normal" font="default" size="100%">T-Cell Acute Lymphocytic Leukemia Protein 1</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Dec 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">4932-46</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Understanding the transcriptional cues that direct differentiation of human embryonic stem cells (hESCs) and human-induced pluripotent stem cells to defined and functional cell types is essential for future clinical applications. In this study, we have compared transcriptional profiles of haematopoietic progenitors derived from hESCs at various developmental stages of a feeder- and serum-free differentiation method and show that the largest transcriptional changes occur during the first 4 days of differentiation. Data mining on the basis of molecular function revealed Rho-GTPase signalling as a key regulator of differentiation. Inhibition of this pathway resulted in a significant reduction in the numbers of emerging haematopoietic progenitors throughout the differentiation window, thereby uncovering a previously unappreciated role for Rho-GTPase signalling during human haematopoietic development. Our analysis indicated that SCL was the 11th most upregulated transcript during the first 4 days of the hESC differentiation process. Overexpression of SCL in hESCs promoted differentiation to meso-endodermal lineages, the emergence of haematopoietic and erythro-megakaryocytic progenitors and accelerated erythroid differentiation. Importantly, intrasplenic transplantation of SCL-overexpressing hESC-derived haematopoietic cells enhanced recovery from induced acute anaemia without significant cell engraftment, suggesting a paracrine-mediated effect.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">24</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21937587?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martín-Trillo, Mar</style></author><author><style face="normal" font="default" size="100%">Grandío, Eduardo González</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Marcel, Fabien</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Buey, María Luisa</style></author><author><style face="normal" font="default" size="100%">Schmitz, Gregor</style></author><author><style face="normal" font="default" size="100%">Theres, Klaus</style></author><author><style face="normal" font="default" size="100%">Bendahmane, Abdelhafid</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Cubas, Pilar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Role of tomato BRANCHED1-like genes in the control of shoot branching.</style></title><secondary-title><style face="normal" font="default" size="100%">The Plant journal : for cell and molecular biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">701-14</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In angiosperms, shoot branching greatly determines overall plant architecture and affects fundamental aspects of plant life. Branching patterns are determined by genetic pathways conserved widely across angiosperms. In Arabidopsis thaliana (Brassicaceae, Rosidae) BRANCHED1 (BRC1) plays a central role in this process, acting locally to arrest axillary bud growth. In tomato (Solanum lycopersicum, Solanaceae, Asteridae) we have identified two BRC1-like paralogues, SlBRC1a and SlBRC1b. These genes are expressed in arrested axillary buds and both are down-regulated upon bud activation, although SlBRC1a is transcribed at much lower levels than SlBRC1b. Alternative splicing of SlBRC1a renders two transcripts that encode two BRC1-like proteins with different C-t domains due to a 3’-terminal frameshift. The phenotype of loss-of-function lines suggests that SlBRC1b has retained the ancestral role of BRC1 in shoot branch suppression. We have isolated the BRC1a and BRC1b genes of other Solanum species and have studied their evolution rates across the lineages. These studies indicate that, after duplication of an ancestral BRC1-like gene, BRC1b genes continued to evolve under a strong purifying selection that was consistent with the conserved function of SlBRC1b in shoot branching control. In contrast, the coding sequences of Solanum BRC1a genes have evolved at a higher evolution rate. Branch-site tests indicate that this difference does not reflect relaxation but rather positive selective pressure for adaptation.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lüke, Lena</style></author><author><style face="normal" font="default" size="100%">Vicens, Alberto</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Luque-Larena, Juan Jose</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Roldan, Eduardo R S</style></author><author><style face="normal" font="default" size="100%">Gomendio, Montserrat</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sexual selection halts the relaxation of protamine 2 among rodents.</style></title><secondary-title><style face="normal" font="default" size="100%">PloS one</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029247</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">e29247</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sexual selection has been proposed as the driving force promoting the rapid evolutionary changes observed in some reproductive genes including protamines. We test this hypothesis in a group of rodents which show marked differences in the intensity of sexual selection. Levels of sperm competition were not associated with the evolutionary rates of protamine 1 but, contrary to expectations, were negatively related to the evolutionary rate of cleaved- and mature-protamine 2. Since both domains were found to be under relaxation, our findings reveal an unforeseen role of sexual selection: to halt the degree of degeneration that proteins within families may experience due to functional redundancy. The degree of relaxation of protamine 2 in this group of rodents is such that in some species it has become dysfunctional and it is not expressed in mature spermatozoa. In contrast, protamine 1 is functionally conserved but shows directed positive selection on specific sites which are functionally relevant such as DNA-anchoring domains and phosphorylation sites. We conclude that in rodents protamine 2 is under relaxation and that sexual selection removes deleterious mutations among species with high levels of sperm competition to maintain the protein functional and the spermatozoa competitive.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cuenca-Bono, Bernardo</style></author><author><style face="normal" font="default" size="100%">García-Molinero, Varinia</style></author><author><style face="normal" font="default" size="100%">Pascual-García, Pau</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Llopis, Ana</style></author><author><style face="normal" font="default" size="100%">Vilardell, Josep</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Navarro, Susana</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SUS1 introns are required for efficient mRNA nuclear export in yeast.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic acids research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Oct 1</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">8599-611</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Efficient coupling between mRNA synthesis and export is essential for gene expression. Sus1/ENY2, a component of the SAGA and TREX-2 complexes, is involved in both transcription and mRNA export. While most yeast genes lack introns, we previously reported that yeast SUS1 bears two. Here we show that this feature is evolutionarily conserved and critical for Sus1 function. We determine that while SUS1 splicing is inefficient, it responds to cellular conditions, and intronic mutations either promoting or blocking splicing lead to defects in mRNA export and cell growth. Consistent with this, we find that an intron-less SUS1 only partially rescues sus1&amp;Delta; phenotypes. Remarkably, splicing of each SUS1 intron is also affected by the presence of the other and by SUS1 exonic sequences. Moreover, by following SUS1 RNA and protein levels we establish that nonsense-mediated decay (NMD) pathway and the splicing factor Mud2 both play a role in SUS1 expression. Our data (and those of the accompanying work by Hossain et al.) provide evidence of the involvement of splicing, translation, and decay in the regulation of early events in mRNP biogenesis; and imply the additional requirement for a balance in splicing isoforms from a single gene.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Javierre, Biola M</style></author><author><style face="normal" font="default" size="100%">Fernandez, Agustin F</style></author><author><style face="normal" font="default" size="100%">Richter, Julia</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Martin-Subero, J Ignacio</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Ubreva, Javier</style></author><author><style face="normal" font="default" size="100%">Berdasco, Maria</style></author><author><style face="normal" font="default" size="100%">Fraga, Mario F</style></author><author><style face="normal" font="default" size="100%">O’Hanlon, Terrance P</style></author><author><style face="normal" font="default" size="100%">Rider, Lisa G</style></author><author><style face="normal" font="default" size="100%">Jacinto, Filipe V</style></author><author><style face="normal" font="default" size="100%">Lopez-Longo, F Javier</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Forn, Marta</style></author><author><style face="normal" font="default" size="100%">Peinado, Miguel A</style></author><author><style face="normal" font="default" size="100%">Carreño, Luis</style></author><author><style face="normal" font="default" size="100%">Sawalha, Amr H</style></author><author><style face="normal" font="default" size="100%">Harley, John B</style></author><author><style face="normal" font="default" size="100%">Siebert, Reiner</style></author><author><style face="normal" font="default" size="100%">Esteller, Manel</style></author><author><style face="normal" font="default" size="100%">Miller, Frederick W</style></author><author><style face="normal" font="default" size="100%">Ballestar, Esteban</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">170-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Monozygotic (MZ) twins are partially concordant for most complex diseases, including autoimmune disorders. Whereas phenotypic concordance can be used to study heritability, discordance suggests the role of non-genetic factors. In autoimmune diseases, environmentally driven epigenetic changes are thought to contribute to their etiology. Here we report the first high-throughput and candidate sequence analyses of DNA methylation to investigate discordance for autoimmune disease in twins. We used a cohort of MZ twins discordant for three diseases whose clinical signs often overlap: systemic lupus erythematosus (SLE), rheumatoid arthritis, and dermatomyositis. Only MZ twins discordant for SLE featured widespread changes in the DNA methylation status of a significant number of genes. Gene ontology analysis revealed enrichment in categories associated with immune function. Individual analysis confirmed the existence of DNA methylation and expression changes in genes relevant to SLE pathogenesis. These changes occurred in parallel with a global decrease in the 5-methylcytosine content that was concomitantly accompanied with changes in DNA methylation and expression levels of ribosomal RNA genes, although no changes in repetitive sequences were found. Our findings not only identify potentially relevant DNA methylation markers for the clinical characterization of SLE patients but also support the notion that epigenetic changes may be critical in the clinical manifestations of autoimmune disease.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bediaga, Naiara G</style></author><author><style face="normal" font="default" size="100%">Acha-Sagredo, Amelia</style></author><author><style face="normal" font="default" size="100%">Guerra, Isabel</style></author><author><style face="normal" font="default" size="100%">Viguri, Amparo</style></author><author><style face="normal" font="default" size="100%">Albaina, Carmen</style></author><author><style face="normal" font="default" size="100%">Ruiz Diaz, Irune</style></author><author><style face="normal" font="default" size="100%">Rezola, Ricardo</style></author><author><style face="normal" font="default" size="100%">Alberdi, Maria Jesus</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Renobales, Mertxe</style></author><author><style face="normal" font="default" size="100%">Fernandez, Agustin F</style></author><author><style face="normal" font="default" size="100%">Field, John K</style></author><author><style face="normal" font="default" size="100%">Fraga, Mario F</style></author><author><style face="normal" font="default" size="100%">Liloglou, Triantafillos</style></author><author><style face="normal" font="default" size="100%">de Pancorbo, Marian M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DNA methylation epigenotypes in breast cancer molecular subtypes.</style></title><secondary-title><style face="normal" font="default" size="100%">Breast Cancer Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Breast Cancer Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Breast Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">CpG Islands</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Methylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenesis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, p53</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Ki-67 Antigen</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Grading</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptor, ErbB-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Tumor Suppressor Protein p53</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">R77</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;INTRODUCTION: &lt;/b&gt;Identification of gene expression based breast cancer subtypes is considered as a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and there is only a limited understanding of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and deliver specific epigenotypes associated with particular breast cancer subtypes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Using a microarray approach we analyzed DNA methylation in regulatory regions of 806 cancer related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biological validation by Pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A and 48 luminal B paired breast cancer/adjacent tissues. Using all-subset selection method, we identified the most subtype predictive methylation profiles in multivariable logistic regression analysis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identify novel subtype specific epigenotypes which clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our results provide evidence that well defined DNA methylation profiles enables breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/20920229?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peña, Arantxa</style></author><author><style face="normal" font="default" size="100%">Teeling, Hanno</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, Jaime</style></author><author><style face="normal" font="default" size="100%">Santos, Fernando</style></author><author><style face="normal" font="default" size="100%">Yarza, Pablo</style></author><author><style face="normal" font="default" size="100%">Brito-Echeverría, Jocelyn</style></author><author><style face="normal" font="default" size="100%">Lucio, Marianna</style></author><author><style face="normal" font="default" size="100%">Schmitt-Kopplin, Philippe</style></author><author><style face="normal" font="default" size="100%">Meseguer, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Schenowitz, Chantal</style></author><author><style face="normal" font="default" size="100%">Dossat, Carole</style></author><author><style face="normal" font="default" size="100%">Barbe, Valerie</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Rosselló-Mora, Ramon</style></author><author><style face="normal" font="default" size="100%">Schüler, Margarete</style></author><author><style face="normal" font="default" size="100%">Glöckner, Frank Oliver</style></author><author><style face="normal" font="default" size="100%">Amann, Rudolf</style></author><author><style face="normal" font="default" size="100%">Gabaldón, Toni</style></author><author><style face="normal" font="default" size="100%">Antón, Josefa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains.</style></title><secondary-title><style face="normal" font="default" size="100%">The ISME journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Feb 18</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Genomic and metagenomic data indicate a high degree of genomic variation within microbial populations, although the ecological and evolutive meaning of this microdiversity remains unknown. Microevolution analyses, including genomic and experimental approaches, are so far very scarce for non-pathogenic bacteria. In this study, we compare the genomes, metabolomes and selected ecological traits of the strains M8 and M31 of the hyperhalophilic bacterium Salinibacter ruber that contain ribosomal RNA (rRNA) gene and intergenic regions that are identical in sequence and were simultaneously isolated from a Mediterranean solar saltern. Comparative analyses indicate that S. ruber genomes present a mosaic structure with conserved and hypervariable regions (HVRs). The HVRs or genomic islands, are enriched in transposases, genes related to surface properties, strain-specific genes and highly divergent orthologous. However, the many indels outside the HVRs indicate that genome plasticity extends beyond them. Overall, 10% of the genes encoded in the M8 genome are absent from M31 and could stem from recent acquisitions. S. ruber genomes also harbor 34 genes located outside HVRs that are transcribed during standard growth and probably derive from lateral gene transfers with Archaea preceding the M8/M31 divergence. Metabolomic analyses, phage susceptibility and competition experiments indicate that these genomic differences cannot be considered neutral from an ecological perspective. The results point to the avoidance of competition by micro-niche adaptation and response to viral predation as putative major forces that drive microevolution within these Salinibacter strains. In addition, this work highlights the extent of bacterial functional diversity and environmental adaptation, beyond the resolution of the 16S rRNA and internal transcribed spacers regions.The ISME Journal advance online publication, 18 February 2010; doi:10.1038/ismej.2010.6.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moreno-Manzano, Victoria</style></author><author><style face="normal" font="default" size="100%">Rodríguez-Jiménez, Francisco J</style></author><author><style face="normal" font="default" size="100%">Aceña-Bonilla, Jose L</style></author><author><style face="normal" font="default" size="100%">Fustero-Lardíes, Santos</style></author><author><style face="normal" font="default" size="100%">Erceg, Slaven</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Stojkovic, Miodrag</style></author><author><style face="normal" font="default" size="100%">Sánchez-Puelles, Jose M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">FM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status.</style></title><secondary-title><style face="normal" font="default" size="100%">The Journal of biological chemistry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Jan 8</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">285</style></volume><pages><style face="normal" font="default" size="100%">1333-42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The biology of the alpha subunits of hypoxia-inducible factors (HIFalpha) has expanded from their role in angiogenesis to their current position in the self-renewal and differentiation of stem cells. The results reported in this article show the discovery of FM19G11, a novel chemical entity that inhibits HIFalpha proteins that repress target genes of the two alpha subunits, in various tumor cell lines as well as in adult and embryonic stem cell models from rodents and humans, respectively. FM19G11 inhibits at nanomolar range the transcriptional and protein expression of Oct4, Sox2, Nanog, and Tgf-alpha undifferentiating factors, in adult rat and human embryonic stem cells, FM19G11 activity occurs in ependymal progenitor stem cells from rats (epSPC), a cell model reported for spinal cord regeneration, which allows the progression of oligodendrocyte cell differentiation in a hypoxic environment, has created interest in its characterization for pharmacological research. Experiments using small interfering RNA showed a significant depletion in Sox2 protein only in the case of HIF2alpha silencing, but not in HIF1alpha-mediated ablation. Moreover, chromatin immunoprecipitation data, together with the significant presence of functional hypoxia response element consensus sequences in the promoter region of Sox2, strongly validated that this factor behaves as a target gene of HIF2alpha in epSPCs. FM19G11 causes a reduction of overall histone acetylation with significant repression of p300, a histone acetyltransferase required as a co-factor for HIF-transcription activation. Arrays carried out in the presence and absence of the inhibitor showed the predominant involvement of epigenetic-associated events mediated by the drug.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Galan, Amparo</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Póo, M Eugenia</style></author><author><style face="normal" font="default" size="100%">Valbuena, Diana</style></author><author><style face="normal" font="default" size="100%">Ruiz, Veronica</style></author><author><style face="normal" font="default" size="100%">Aguilar, Cristóbal</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Simon, Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Functional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS One</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Blastomeres</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Complementary</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Oct 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">e13615</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Blastomere fate and embryonic genome activation (EGA) during human embryonic development are unsolved areas of high scientific and clinical interest. Forty-nine blastomeres from 5- to 8-cell human embryos have been investigated following an efficient single-cell cDNA amplification protocol to provide a template for high-density microarray analysis. The previously described markers, characteristic of Inner Cell Mass (ICM) (n = 120), stemness (n = 190) and Trophectoderm (TE) (n = 45), were analyzed, and a housekeeping pattern of 46 genes was established. All the human blastomeres from the 5- to 8-cell stage embryo displayed a common gene expression pattern corresponding to ICM markers (e.g., DDX3, FOXD3, LEFTY1, MYC, NANOG, POU5F1), stemness (e.g., POU5F1, DNMT3B, GABRB3, SOX2, ZFP42, TERT), and TE markers (e.g., GATA6, EOMES, CDX2, LHCGR). The EGA profile was also investigated between the 5-6- and 8-cell stage embryos, and compared to the blastocyst stage. Known genes (n = 92) such as depleted maternal transcripts (e.g., CCNA1, CCNB1, DPPA2) and embryo-specific activation (e.g., POU5F1, CDH1, DPPA4), as well as novel genes, were confirmed. In summary, the global single-cell cDNA amplification microarray analysis of the 5- to 8-cell stage human embryos reveals that blastomere fate is not committed to ICM or TE. Finally, new EGA features in human embryogenesis are presented.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/21049019?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shi, Leming</style></author><author><style face="normal" font="default" size="100%">Campbell, Gregory</style></author><author><style face="normal" font="default" size="100%">Jones, Wendell D</style></author><author><style face="normal" font="default" size="100%">Campagne, Fabien</style></author><author><style face="normal" font="default" size="100%">Wen, Zhining</style></author><author><style face="normal" font="default" size="100%">Walker, Stephen J</style></author><author><style face="normal" font="default" size="100%">Su, Zhenqiang</style></author><author><style face="normal" font="default" size="100%">Chu, Tzu-Ming</style></author><author><style face="normal" font="default" size="100%">Goodsaid, Federico M</style></author><author><style face="normal" font="default" size="100%">Pusztai, Lajos</style></author><author><style face="normal" font="default" size="100%">Shaughnessy, John D</style></author><author><style face="normal" font="default" size="100%">Oberthuer, André</style></author><author><style face="normal" font="default" size="100%">Thomas, Russell S</style></author><author><style face="normal" font="default" size="100%">Paules, Richard S</style></author><author><style face="normal" font="default" size="100%">Fielden, Mark</style></author><author><style face="normal" font="default" size="100%">Barlogie, Bart</style></author><author><style face="normal" font="default" size="100%">Chen, Weijie</style></author><author><style face="normal" font="default" size="100%">Du, Pan</style></author><author><style face="normal" font="default" size="100%">Fischer, Matthias</style></author><author><style face="normal" font="default" size="100%">Furlanello, Cesare</style></author><author><style face="normal" font="default" size="100%">Gallas, Brandon D</style></author><author><style face="normal" font="default" size="100%">Ge, Xijin</style></author><author><style face="normal" font="default" size="100%">Megherbi, Dalila B</style></author><author><style face="normal" font="default" size="100%">Symmans, W Fraser</style></author><author><style face="normal" font="default" size="100%">Wang, May D</style></author><author><style face="normal" font="default" size="100%">Zhang, John</style></author><author><style face="normal" font="default" size="100%">Bitter, Hans</style></author><author><style face="normal" font="default" size="100%">Brors, Benedikt</style></author><author><style face="normal" font="default" size="100%">Bushel, Pierre R</style></author><author><style face="normal" font="default" size="100%">Bylesjo, Max</style></author><author><style face="normal" font="default" size="100%">Chen, Minjun</style></author><author><style face="normal" font="default" size="100%">Cheng, Jie</style></author><author><style face="normal" font="default" size="100%">Cheng, Jing</style></author><author><style face="normal" font="default" size="100%">Chou, Jeff</style></author><author><style face="normal" font="default" size="100%">Davison, Timothy S</style></author><author><style face="normal" font="default" size="100%">Delorenzi, Mauro</style></author><author><style face="normal" font="default" size="100%">Deng, Youping</style></author><author><style face="normal" font="default" size="100%">Devanarayan, Viswanath</style></author><author><style face="normal" font="default" size="100%">Dix, David J</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Dorff, Kevin C</style></author><author><style face="normal" font="default" size="100%">Elloumi, Fathi</style></author><author><style face="normal" font="default" size="100%">Fan, Jianqing</style></author><author><style face="normal" font="default" size="100%">Fan, Shicai</style></author><author><style face="normal" font="default" size="100%">Fan, Xiaohui</style></author><author><style face="normal" font="default" size="100%">Fang, Hong</style></author><author><style face="normal" font="default" size="100%">Gonzaludo, Nina</style></author><author><style face="normal" font="default" size="100%">Hess, Kenneth R</style></author><author><style face="normal" font="default" size="100%">Hong, Huixiao</style></author><author><style face="normal" font="default" size="100%">Huan, Jun</style></author><author><style face="normal" font="default" size="100%">Irizarry, Rafael A</style></author><author><style face="normal" font="default" size="100%">Judson, Richard</style></author><author><style face="normal" font="default" size="100%">Juraeva, Dilafruz</style></author><author><style face="normal" font="default" size="100%">Lababidi, Samir</style></author><author><style face="normal" font="default" size="100%">Lambert, Christophe G</style></author><author><style face="normal" font="default" size="100%">Li, Li</style></author><author><style face="normal" font="default" size="100%">Li, Yanen</style></author><author><style face="normal" font="default" size="100%">Li, Zhen</style></author><author><style face="normal" font="default" size="100%">Lin, Simon M</style></author><author><style face="normal" font="default" size="100%">Liu, Guozhen</style></author><author><style face="normal" font="default" size="100%">Lobenhofer, Edward K</style></author><author><style face="normal" font="default" size="100%">Luo, Jun</style></author><author><style face="normal" font="default" size="100%">Luo, Wen</style></author><author><style face="normal" font="default" size="100%">McCall, Matthew N</style></author><author><style face="normal" font="default" size="100%">Nikolsky, Yuri</style></author><author><style face="normal" font="default" size="100%">Pennello, Gene A</style></author><author><style face="normal" font="default" size="100%">Perkins, Roger G</style></author><author><style face="normal" font="default" size="100%">Philip, Reena</style></author><author><style face="normal" font="default" size="100%">Popovici, Vlad</style></author><author><style face="normal" font="default" size="100%">Price, Nathan D</style></author><author><style face="normal" font="default" size="100%">Qian, Feng</style></author><author><style face="normal" font="default" size="100%">Scherer, Andreas</style></author><author><style face="normal" font="default" size="100%">Shi, Tieliu</style></author><author><style face="normal" font="default" size="100%">Shi, Weiwei</style></author><author><style face="normal" font="default" size="100%">Sung, Jaeyun</style></author><author><style face="normal" font="default" size="100%">Thierry-Mieg, Danielle</style></author><author><style face="normal" font="default" size="100%">Thierry-Mieg, Jean</style></author><author><style face="normal" font="default" size="100%">Thodima, Venkata</style></author><author><style face="normal" font="default" size="100%">Trygg, Johan</style></author><author><style face="normal" font="default" size="100%">Vishnuvajjala, Lakshmi</style></author><author><style face="normal" font="default" size="100%">Wang, Sue Jane</style></author><author><style face="normal" font="default" size="100%">Wu, Jianping</style></author><author><style face="normal" font="default" size="100%">Wu, Yichao</style></author><author><style face="normal" font="default" size="100%">Xie, Qian</style></author><author><style face="normal" font="default" size="100%">Yousef, Waleed A</style></author><author><style face="normal" font="default" size="100%">Zhang, Liang</style></author><author><style face="normal" font="default" size="100%">Zhang, Xuegong</style></author><author><style face="normal" font="default" size="100%">Zhong, Sheng</style></author><author><style face="normal" font="default" size="100%">Zhou, Yiming</style></author><author><style face="normal" font="default" size="100%">Zhu, Sheng</style></author><author><style face="normal" font="default" size="100%">Arasappan, Dhivya</style></author><author><style face="normal" font="default" size="100%">Bao, Wenjun</style></author><author><style face="normal" font="default" size="100%">Lucas, Anne Bergstrom</style></author><author><style face="normal" font="default" size="100%">Berthold, Frank</style></author><author><style face="normal" font="default" size="100%">Brennan, Richard J</style></author><author><style face="normal" font="default" size="100%">Buness, Andreas</style></author><author><style face="normal" font="default" size="100%">Catalano, Jennifer G</style></author><author><style face="normal" font="default" size="100%">Chang, Chang</style></author><author><style face="normal" font="default" size="100%">Chen, Rong</style></author><author><style face="normal" font="default" size="100%">Cheng, Yiyu</style></author><author><style face="normal" font="default" size="100%">Cui, Jian</style></author><author><style face="normal" font="default" size="100%">Czika, Wendy</style></author><author><style face="normal" font="default" size="100%">Demichelis, Francesca</style></author><author><style face="normal" font="default" size="100%">Deng, Xutao</style></author><author><style face="normal" font="default" size="100%">Dosymbekov, Damir</style></author><author><style face="normal" font="default" size="100%">Eils, Roland</style></author><author><style face="normal" font="default" size="100%">Feng, Yang</style></author><author><style face="normal" font="default" size="100%">Fostel, Jennifer</style></author><author><style face="normal" font="default" size="100%">Fulmer-Smentek, Stephanie</style></author><author><style face="normal" font="default" size="100%">Fuscoe, James C</style></author><author><style face="normal" font="default" size="100%">Gatto, Laurent</style></author><author><style face="normal" font="default" size="100%">Ge, Weigong</style></author><author><style face="normal" font="default" size="100%">Goldstein, Darlene R</style></author><author><style face="normal" font="default" size="100%">Guo, Li</style></author><author><style face="normal" font="default" size="100%">Halbert, Donald N</style></author><author><style face="normal" font="default" size="100%">Han, Jing</style></author><author><style face="normal" font="default" size="100%">Harris, Stephen C</style></author><author><style face="normal" font="default" size="100%">Hatzis, Christos</style></author><author><style face="normal" font="default" size="100%">Herman, Damir</style></author><author><style face="normal" font="default" size="100%">Huang, Jianping</style></author><author><style face="normal" font="default" size="100%">Jensen, Roderick V</style></author><author><style face="normal" font="default" size="100%">Jiang, Rui</style></author><author><style face="normal" font="default" size="100%">Johnson, Charles D</style></author><author><style face="normal" font="default" size="100%">Jurman, Giuseppe</style></author><author><style face="normal" font="default" size="100%">Kahlert, Yvonne</style></author><author><style face="normal" font="default" size="100%">Khuder, Sadik A</style></author><author><style face="normal" font="default" size="100%">Kohl, Matthias</style></author><author><style face="normal" font="default" size="100%">Li, Jianying</style></author><author><style face="normal" font="default" size="100%">Li, Li</style></author><author><style face="normal" font="default" size="100%">Li, Menglong</style></author><author><style face="normal" font="default" size="100%">Li, Quan-Zhen</style></author><author><style face="normal" font="default" size="100%">Li, Shao</style></author><author><style face="normal" font="default" size="100%">Li, Zhiguang</style></author><author><style face="normal" font="default" size="100%">Liu, Jie</style></author><author><style face="normal" font="default" size="100%">Liu, Ying</style></author><author><style face="normal" font="default" size="100%">Liu, Zhichao</style></author><author><style face="normal" font="default" size="100%">Meng, Lu</style></author><author><style face="normal" font="default" size="100%">Madera, Manuel</style></author><author><style face="normal" font="default" size="100%">Martinez-Murillo, Francisco</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Meehan, Joseph</style></author><author><style face="normal" font="default" size="100%">Miclaus, Kelci</style></author><author><style face="normal" font="default" size="100%">Moffitt, Richard A</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Mukherjee, Piali</style></author><author><style face="normal" font="default" size="100%">Mulligan, George J</style></author><author><style face="normal" font="default" size="100%">Neville, Padraic</style></author><author><style face="normal" font="default" size="100%">Nikolskaya, Tatiana</style></author><author><style face="normal" font="default" size="100%">Ning, Baitang</style></author><author><style face="normal" font="default" size="100%">Page, Grier P</style></author><author><style face="normal" font="default" size="100%">Parker, Joel</style></author><author><style face="normal" font="default" size="100%">Parry, R Mitchell</style></author><author><style face="normal" font="default" size="100%">Peng, Xuejun</style></author><author><style face="normal" font="default" size="100%">Peterson, Ron L</style></author><author><style face="normal" font="default" size="100%">Phan, John H</style></author><author><style face="normal" font="default" size="100%">Quanz, Brian</style></author><author><style face="normal" font="default" size="100%">Ren, Yi</style></author><author><style face="normal" font="default" size="100%">Riccadonna, Samantha</style></author><author><style face="normal" font="default" size="100%">Roter, Alan H</style></author><author><style face="normal" font="default" size="100%">Samuelson, Frank W</style></author><author><style face="normal" font="default" size="100%">Schumacher, Martin M</style></author><author><style face="normal" font="default" size="100%">Shambaugh, Joseph D</style></author><author><style face="normal" font="default" size="100%">Shi, Qiang</style></author><author><style face="normal" font="default" size="100%">Shippy, Richard</style></author><author><style face="normal" font="default" size="100%">Si, Shengzhu</style></author><author><style face="normal" font="default" size="100%">Smalter, Aaron</style></author><author><style face="normal" font="default" size="100%">Sotiriou, Christos</style></author><author><style face="normal" font="default" size="100%">Soukup, Mat</style></author><author><style face="normal" font="default" size="100%">Staedtler, Frank</style></author><author><style face="normal" font="default" size="100%">Steiner, Guido</style></author><author><style face="normal" font="default" size="100%">Stokes, Todd H</style></author><author><style face="normal" font="default" size="100%">Sun, Qinglan</style></author><author><style face="normal" font="default" size="100%">Tan, Pei-Yi</style></author><author><style face="normal" font="default" size="100%">Tang, Rong</style></author><author><style face="normal" font="default" size="100%">Tezak, Zivana</style></author><author><style face="normal" font="default" size="100%">Thorn, Brett</style></author><author><style face="normal" font="default" size="100%">Tsyganova, Marina</style></author><author><style face="normal" font="default" size="100%">Turpaz, Yaron</style></author><author><style face="normal" font="default" size="100%">Vega, Silvia C</style></author><author><style face="normal" font="default" size="100%">Visintainer, Roberto</style></author><author><style face="normal" font="default" size="100%">von Frese, Juergen</style></author><author><style face="normal" font="default" size="100%">Wang, Charles</style></author><author><style face="normal" font="default" size="100%">Wang, Eric</style></author><author><style face="normal" font="default" size="100%">Wang, Junwei</style></author><author><style face="normal" font="default" size="100%">Wang, Wei</style></author><author><style face="normal" font="default" size="100%">Westermann, Frank</style></author><author><style face="normal" font="default" size="100%">Willey, James C</style></author><author><style face="normal" font="default" size="100%">Woods, Matthew</style></author><author><style face="normal" font="default" size="100%">Wu, Shujian</style></author><author><style face="normal" font="default" size="100%">Xiao, Nianqing</style></author><author><style face="normal" font="default" size="100%">Xu, Joshua</style></author><author><style face="normal" font="default" size="100%">Xu, Lei</style></author><author><style face="normal" font="default" size="100%">Yang, Lun</style></author><author><style face="normal" font="default" size="100%">Zeng, Xiao</style></author><author><style face="normal" font="default" size="100%">Zhang, Jialu</style></author><author><style face="normal" font="default" size="100%">Zhang, Li</style></author><author><style face="normal" font="default" size="100%">Zhang, Min</style></author><author><style face="normal" font="default" size="100%">Zhao, Chen</style></author><author><style face="normal" font="default" size="100%">Puri, Raj K</style></author><author><style face="normal" font="default" size="100%">Scherf, Uwe</style></author><author><style face="normal" font="default" size="100%">Tong, Weida</style></author><author><style face="normal" font="default" size="100%">Wolfinger, Russell D</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature biotechnology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Aug</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">827-38</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, &amp;gt;30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rattei, Thomas</style></author><author><style face="normal" font="default" size="100%">Tischler, Patrick</style></author><author><style face="normal" font="default" size="100%">Götz, Stefan</style></author><author><style face="normal" font="default" size="100%">Jehl, Marc-André</style></author><author><style face="normal" font="default" size="100%">Hoser, Jonathan</style></author><author><style face="normal" font="default" size="100%">Arnold, Roland</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Mewes, Hans-Werner</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SIMAP–a comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic acids research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">38</style></volume><pages><style face="normal" font="default" size="100%">D223-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date pre-calculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are pre-calculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aggarwal, Mohit</style></author><author><style face="normal" font="default" size="100%">Sánchez-Beato, Margarita</style></author><author><style face="normal" font="default" size="100%">Gómez-López, Gonzalo</style></author><author><style face="normal" font="default" size="100%">Al-Shahrour, Fátima</style></author><author><style face="normal" font="default" size="100%">Martínez, Nerea</style></author><author><style face="normal" font="default" size="100%">Rodríguez, Antonia</style></author><author><style face="normal" font="default" size="100%">Ruiz-Ballesteros, Elena</style></author><author><style face="normal" font="default" size="100%">Camacho, Francisca I</style></author><author><style face="normal" font="default" size="100%">Pérez-Rosado, Alberto</style></author><author><style face="normal" font="default" size="100%">de la Cueva, Paloma</style></author><author><style face="normal" font="default" size="100%">Artiga, María J</style></author><author><style face="normal" font="default" size="100%">Pisano, David G</style></author><author><style face="normal" font="default" size="100%">Kimby, Eva</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Villuendas, Raquel</style></author><author><style face="normal" font="default" size="100%">Piris, Miguel A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Functional signatures identified in B-cell non-Hodgkin lymphoma profiles.</style></title><secondary-title><style face="normal" font="default" size="100%">Leuk Lymphoma</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Leuk Lymphoma</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Leukemic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Heterogeneity</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Lymphoma, B-Cell</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">1699-708</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Gene-expression profiling in B-cell lymphomas has provided crucial data on specific lymphoma types, which can contribute to the identification of essential lymphoma survival genes and pathways. In this study, the gene-expression profiling data of all major B-cell lymphoma types were analyzed by unsupervised clustering. The transcriptome classification so obtained, was explored using gene set enrichment analysis generating a heatmap for B-cell lymphoma that identifies common lymphoma survival mechanisms and potential therapeutic targets, recognizing sets of coregulated genes and functional pathways expressed in different lymphoma types. Some of the most relevant signatures (stroma, cell cycle, B-cell receptor (BCR)) are shared by multiple lymphoma types or subclasses. A specific attention was paid to the analysis of BCR and coregulated pathways, defining molecular heterogeneity within multiple B-cell lymphoma types.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/19863341?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Orti, L.</style></author><author><style face="normal" font="default" size="100%">Carbajo, R. J.</style></author><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Maurer, S. M.</style></author><author><style face="normal" font="default" size="100%">Rai, A. K.</style></author><author><style face="normal" font="default" size="100%">Taylor, G.</style></author><author><style face="normal" font="default" size="100%">Todd, M. H.</style></author><author><style face="normal" font="default" size="100%">Pineda-Lucena, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A kernel for open source drug discovery in tropical diseases</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Negl Trop Dis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19381286</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e418</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&amp;D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such &quot;kernels&quot;. METHODOLOGY/PRINCIPAL FINDINGS: HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. CONCLUSIONS/SIGNIFICANCE: The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.</style></abstract><notes><style face="normal" font="default" size="100%">Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A United States PLoS neglected tropical diseases PLoS Negl Trop Dis. 2009;3(4):e418. Epub 2009 Apr 21.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Orti, L.</style></author><author><style face="normal" font="default" size="100%">Carbajo, R. J.</style></author><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Maurer, S. M.</style></author><author><style face="normal" font="default" size="100%">Rai, A. K.</style></author><author><style face="normal" font="default" size="100%">Taylor, G.</style></author><author><style face="normal" font="default" size="100%">Todd, M. H.</style></author><author><style face="normal" font="default" size="100%">Pineda-Lucena, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A kernel for the Tropical Disease Initiative</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Biotechnol</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19352362</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">320-1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">&lt;p&gt;Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A P01 AI035707/AI/NIAID NIH HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t United States Nature biotechnology Nat Biotechnol. 2009 Apr;27(4):320-1.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andrew R Jones</style></author><author><style face="normal" font="default" size="100%">Allyson L Lister</style></author><author><style face="normal" font="default" size="100%">Leandro Hermida</style></author><author><style face="normal" font="default" size="100%">Peter Wilkinson</style></author><author><style face="normal" font="default" size="100%">Martin Eisenacher</style></author><author><style face="normal" font="default" size="100%">Khalid Belhajjame</style></author><author><style face="normal" font="default" size="100%">Frank Gibson</style></author><author><style face="normal" font="default" size="100%">Phil Lord</style></author><author><style face="normal" font="default" size="100%">Matthew Pocock</style></author><author><style face="normal" font="default" size="100%">Heiko Rosenfelder</style></author><author><style face="normal" font="default" size="100%">Santoyo-López, Javier</style></author><author><style face="normal" font="default" size="100%">Anil Wipat</style></author><author><style face="normal" font="default" size="100%">Norman W Paton</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling and managing experimental data using FuGE.</style></title><secondary-title><style face="normal" font="default" size="100%">OMICS</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">239-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Johan H van Heerden</style></author><author><style face="normal" font="default" size="100%">Ana Conesa</style></author><author><style face="normal" font="default" size="100%">Dan J Stein</style></author><author><style face="normal" font="default" size="100%">Montaner, David</style></author><author><style face="normal" font="default" size="100%">Vivienne Russell</style></author><author><style face="normal" font="default" size="100%">Nicola Illing</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parallel changes in gene expression in peripheral blood mononuclear cells and the brain after maternal separation in the mouse.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Res Notes</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">195</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reiss, JO</style></author><author><style face="normal" font="default" size="100%">Burke, A C</style></author><author><style face="normal" font="default" size="100%">Archer, C</style></author><author><style face="normal" font="default" size="100%">De Renzi, M</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Etxeberria, A</style></author><author><style face="normal" font="default" size="100%">Gale, E A</style></author><author><style face="normal" font="default" size="100%">Hinchliffe, J R</style></author><author><style face="normal" font="default" size="100%">Nuño de la Rosa, L</style></author><author><style face="normal" font="default" size="100%">Rose, C S</style></author><author><style face="normal" font="default" size="100%">Rasskin-Gutman, D</style></author><author><style face="normal" font="default" size="100%">Müller, G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pere Alberch: Originator of EvoDevo</style></title><secondary-title><style face="normal" font="default" size="100%">Biological Theory</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">351-353</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin-Coello, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Ausio, J.</style></author><author><style face="normal" font="default" size="100%">Roldan, E. R.</style></author><author><style face="normal" font="default" size="100%">Gomendio, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sexual selection drives weak positive selection in protamine genes and high promoter divergence, enhancing sperm competitiveness</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Biol Sci</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">positive selection</style></keyword><keyword><style  face="normal" font="default" size="100%">sperm competition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19364735</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Phenotypic adaptations may be the result of changes in gene structure or gene regulation, but little is known about the evolution of gene expression. In addition, it is unclear whether the same selective forces may operate at both levels simultaneously. Reproductive proteins evolve rapidly, but the underlying selective forces promoting such rapid changes are still a matter of debate. In particular, the role of sexual selection in driving positive selection among reproductive proteins remains controversial, whereas its potential influence on changes in promoter regions has not been explored. Protamines are responsible for maintaining DNA in a compacted form in chromosomes in sperm and the available evidence suggests that they evolve rapidly. Because protamines condense DNA within the sperm nucleus, they influence sperm head shape. Here, we examine the influence of sperm competition upon protamine 1 and protamine 2 genes and their promoters, by comparing closely related species of Mus that differ in relative testes size, a reliable indicator of levels of sperm competition. We find evidence of positive selection in the protamine 2 gene in the species with the highest inferred levels of sperm competition. In addition, sperm competition levels across all species are strongly associated with high divergence in protamine 2 promoters that, in turn, are associated with sperm swimming speed. We suggest that changes in protamine 2 promoters are likely to enhance sperm swimming speed by making sperm heads more hydrodynamic. Such phenotypic changes are adaptive because sperm swimming speed may be a major determinant of fertilization success under sperm competition. Thus, when species have diverged recently, few changes in gene-coding sequences are found, while high divergence in promoters seems to be associated with the intensity of sexual selection.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Journal article Proceedings. Biological sciences / The Royal Society Proc Biol Sci. 2009 Apr 8.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bonifaci, N.</style></author><author><style face="normal" font="default" size="100%">Berenguer, A.</style></author><author><style face="normal" font="default" size="100%">Diez, J.</style></author><author><style face="normal" font="default" size="100%">Reina, O.</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Moreno, V.</style></author><author><style face="normal" font="default" size="100%">Pujana, M. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Med Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">gene set</style></keyword><keyword><style  face="normal" font="default" size="100%">GWAS</style></keyword><keyword><style  face="normal" font="default" size="100%">SNP</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19094230</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">62</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;ABSTRACT: BACKGROUND: Recent advances in whole-genome association studies (WGASs) for human cancer risk are beginning to provide the part lists of low-penetrance susceptibility genes. However, statistical analysis in these studies is complicated by the vast number of genetic variants examined and the weak effects observed, as a result of which constraints must be incorporated into the study design and analytical approach. In this scenario, biological attributes beyond the adjusted statistics generally receive little attention and, more importantly, the fundamental biological characteristics of low-penetrance susceptibility genes have yet to be determined. METHODS: We applied an integrative approach for identifying candidate low-penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. RESULTS: First, examination of the distribution of Gene Ontology terms in ordered WGAS results identified asymmetrical distribution of Cell Communication and Cell Death processes linked to risk. Second, analysis of 11 different types of molecular or functional relationships in genomic and proteomic data sets defined the &amp;quot;omic&amp;quot; properties of candidate genes: i/ differential expression in tumors relative to normal tissue; ii/ somatic genomic copy number changes correlating with gene expression levels; iii/ differentially expressed across age at diagnosis; and iv/ expression changes after BRCA1 perturbation. Finally, network modeling of the effects of variants on germline gene expression showed higher connectivity than expected by chance between novel candidates and with known susceptibility genes, which supports functional relationships and provides mechanistic hypotheses of risk. CONCLUSION: This study proposes that cell communication and cell death are major biological processes perturbed in risk of breast cancer conferred by low-penetrance variants, and defines the common omic properties, molecular interactions and possible functional effects of candidate genes and proteins.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Bonifaci, Nuria Berenguer, Antoni Diez, Javier Reina, Oscar Medina, Ignacio Dopazo, Joaquin Moreno, Victor Pujana, Miguel Angel England BMC medical genomics BMC Med Genomics. 2008 Dec 18;1:62.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Götz, Stefan</style></author><author><style face="normal" font="default" size="100%">García-Gómez, Juan Miguel</style></author><author><style face="normal" font="default" size="100%">Terol, Javier</style></author><author><style face="normal" font="default" size="100%">Williams, Tim D</style></author><author><style face="normal" font="default" size="100%">Nagaraj, Shivashankar H</style></author><author><style face="normal" font="default" size="100%">Nueda, Maria José</style></author><author><style face="normal" font="default" size="100%">Robles, Montserrat</style></author><author><style face="normal" font="default" size="100%">Talon, Manuel</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Conesa, Ana</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">High-throughput functional annotation and data mining with the Blast2GO suite.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Graphics</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Expressed Sequence Tags</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Vocabulary, Controlled</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">3420-35</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/18445632?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wilkinson, Mark D</style></author><author><style face="normal" font="default" size="100%">Senger, Martin</style></author><author><style face="normal" font="default" size="100%">Kawas, Edward</style></author><author><style face="normal" font="default" size="100%">Bruskiewich, Richard</style></author><author><style face="normal" font="default" size="100%">Gouzy, Jerome</style></author><author><style face="normal" font="default" size="100%">Noirot, Celine</style></author><author><style face="normal" font="default" size="100%">Bardou, Philippe</style></author><author><style face="normal" font="default" size="100%">Ng, Ambrose</style></author><author><style face="normal" font="default" size="100%">Haase, Dirk</style></author><author><style face="normal" font="default" size="100%">Saiz, Enrique de Andres</style></author><author><style face="normal" font="default" size="100%">Wang, Dennis</style></author><author><style face="normal" font="default" size="100%">Gibbons, Frank</style></author><author><style face="normal" font="default" size="100%">Gordon, Paul M K</style></author><author><style face="normal" font="default" size="100%">Sensen, Christoph W</style></author><author><style face="normal" font="default" size="100%">Carrasco, Jose Manuel Rodriguez</style></author><author><style face="normal" font="default" size="100%">Fernández, José M</style></author><author><style face="normal" font="default" size="100%">Shen, Lixin</style></author><author><style face="normal" font="default" size="100%">Links, Matthew</style></author><author><style face="normal" font="default" size="100%">Ng, Michael</style></author><author><style face="normal" font="default" size="100%">Opushneva, Nina</style></author><author><style face="normal" font="default" size="100%">Neerincx, Pieter B T</style></author><author><style face="normal" font="default" size="100%">Leunissen, Jack A M</style></author><author><style face="normal" font="default" size="100%">Ernst, Rebecca</style></author><author><style face="normal" font="default" size="100%">Twigger, Simon</style></author><author><style face="normal" font="default" size="100%">Usadel, Bjorn</style></author><author><style face="normal" font="default" size="100%">Good, Benjamin</style></author><author><style face="normal" font="default" size="100%">Wong, Yan</style></author><author><style face="normal" font="default" size="100%">Stein, Lincoln</style></author><author><style face="normal" font="default" size="100%">Crosby, William</style></author><author><style face="normal" font="default" size="100%">Karlsson, Johan</style></author><author><style face="normal" font="default" size="100%">Royo, Romina</style></author><author><style face="normal" font="default" size="100%">Párraga, Iván</style></author><author><style face="normal" font="default" size="100%">Ramírez, Sergio</style></author><author><style face="normal" font="default" size="100%">Gelpi, Josep Lluis</style></author><author><style face="normal" font="default" size="100%">Trelles, Oswaldo</style></author><author><style face="normal" font="default" size="100%">Pisano, David G</style></author><author><style face="normal" font="default" size="100%">Jimenez, Natalia</style></author><author><style face="normal" font="default" size="100%">Kerhornou, Arnaud</style></author><author><style face="normal" font="default" size="100%">Rosset, Roman</style></author><author><style face="normal" font="default" size="100%">Zamacola, Leire</style></author><author><style face="normal" font="default" size="100%">Tárraga, Joaquín</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, Jaime</style></author><author><style face="normal" font="default" size="100%">Carazo, Jose María</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author><author><style face="normal" font="default" size="100%">Orozco, Modesto</style></author><author><style face="normal" font="default" size="100%">Valencia, Alfonso</style></author><author><style face="normal" font="default" size="100%">Claros, M Gonzalo</style></author><author><style face="normal" font="default" size="100%">Pérez, Antonio J</style></author><author><style face="normal" font="default" size="100%">Aldana, Jose</style></author><author><style face="normal" font="default" size="100%">Rojano, M  Mar</style></author><author><style face="normal" font="default" size="100%">Fernandez-Santa Cruz, Raul</style></author><author><style face="normal" font="default" size="100%">Navas, Ismael</style></author><author><style face="normal" font="default" size="100%">Schiltz, Gary</style></author><author><style face="normal" font="default" size="100%">Farmer, Andrew</style></author><author><style face="normal" font="default" size="100%">Gessler, Damian</style></author><author><style face="normal" font="default" size="100%">Schoof, Heiko</style></author><author><style face="normal" font="default" size="100%">Groscurth, Andreas</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">BioMoby Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Interoperability with Moby 1.0--it's better than sharing your toothbrush!</style></title><secondary-title><style face="normal" font="default" size="100%">Brief Bioinform</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Brief Bioinform</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Database Management Systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Factual</style></keyword><keyword><style  face="normal" font="default" size="100%">Information Storage and Retrieval</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Programming Languages</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems Integration</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">220-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/18238804?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wilkinson, M. D.</style></author><author><style face="normal" font="default" size="100%">Senger, M.</style></author><author><style face="normal" font="default" size="100%">Kawas, E.</style></author><author><style face="normal" font="default" size="100%">Bruskiewich, R.</style></author><author><style face="normal" font="default" size="100%">Gouzy, J.</style></author><author><style face="normal" font="default" size="100%">Noirot, C.</style></author><author><style face="normal" font="default" size="100%">Bardou, P.</style></author><author><style face="normal" font="default" size="100%">Ng, A.</style></author><author><style face="normal" font="default" size="100%">Haase, D.</style></author><author><style face="normal" font="default" size="100%">Saiz Ede, A.</style></author><author><style face="normal" font="default" size="100%">Wang, D.</style></author><author><style face="normal" font="default" size="100%">Gibbons, F.</style></author><author><style face="normal" font="default" size="100%">Gordon, P. M.</style></author><author><style face="normal" font="default" size="100%">Sensen, C. W.</style></author><author><style face="normal" font="default" size="100%">Carrasco, J. M.</style></author><author><style face="normal" font="default" size="100%">Fernandez, J. M.</style></author><author><style face="normal" font="default" size="100%">Shen, L.</style></author><author><style face="normal" font="default" size="100%">Links, M.</style></author><author><style face="normal" font="default" size="100%">Ng, M.</style></author><author><style face="normal" font="default" size="100%">Opushneva, N.</style></author><author><style face="normal" font="default" size="100%">Neerincx, P. B.</style></author><author><style face="normal" font="default" size="100%">Leunissen, J. A.</style></author><author><style face="normal" font="default" size="100%">Ernst, R.</style></author><author><style face="normal" font="default" size="100%">Twigger, S.</style></author><author><style face="normal" font="default" size="100%">Usadel, B.</style></author><author><style face="normal" font="default" size="100%">Good, B.</style></author><author><style face="normal" font="default" size="100%">Wong, Y.</style></author><author><style face="normal" font="default" size="100%">Stein, L.</style></author><author><style face="normal" font="default" size="100%">Crosby, W.</style></author><author><style face="normal" font="default" size="100%">Karlsson, J.</style></author><author><style face="normal" font="default" size="100%">Royo, R.</style></author><author><style face="normal" font="default" size="100%">Parraga, I.</style></author><author><style face="normal" font="default" size="100%">Ramirez, S.</style></author><author><style face="normal" font="default" size="100%">Gelpi, J. L.</style></author><author><style face="normal" font="default" size="100%">Trelles, O.</style></author><author><style face="normal" font="default" size="100%">Pisano, D. G.</style></author><author><style face="normal" font="default" size="100%">Jimenez, N.</style></author><author><style face="normal" font="default" size="100%">Kerhornou, A.</style></author><author><style face="normal" font="default" size="100%">Rosset, R.</style></author><author><style face="normal" font="default" size="100%">Zamacola, L.</style></author><author><style face="normal" font="default" size="100%">Tarraga, J.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Carazo, J. M.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">R. Guigo</style></author><author><style face="normal" font="default" size="100%">Navarro, A.</style></author><author><style face="normal" font="default" size="100%">Orozco, M.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Claros, M. G.</style></author><author><style face="normal" font="default" size="100%">Perez, A. J.</style></author><author><style face="normal" font="default" size="100%">Aldana, J.</style></author><author><style face="normal" font="default" size="100%">Rojano, M. M.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Santa Cruz, R.</style></author><author><style face="normal" font="default" size="100%">Navas, I.</style></author><author><style face="normal" font="default" size="100%">Schiltz, G.</style></author><author><style face="normal" font="default" size="100%">Farmer, A.</style></author><author><style face="normal" font="default" size="100%">Gessler, D.</style></author><author><style face="normal" font="default" size="100%">Schoof, H.</style></author><author><style face="normal" font="default" size="100%">Groscurth, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interoperability with Moby 1.0–it’s better than sharing your toothbrush!</style></title><secondary-title><style face="normal" font="default" size="100%">Brief Bioinform</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology/*methods *Database Management Systems *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Factual Information Storage and Retrieval/*methods *Internet *Programming Languages Systems Integration</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=18238804</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">220-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;BioMoby Consortium Wilkinson, Mark D Senger, Martin Kawas, Edward Bruskiewich, Richard Gouzy, Jerome Noirot, Celine Bardou, Philippe Ng, Ambrose Haase, Dirk Saiz, Enrique de Andres Wang, Dennis Gibbons, Frank Gordon, Paul M K Sensen, Christoph W Carrasco, Jose Manuel Rodriguez Fernandez, Jose M Shen, Lixin Links, Matthew Ng, Michael Opushneva, Nina Neerincx, Pieter B T Leunissen, Jack A M Ernst, Rebecca Twigger, Simon Usadel, Bjorn Good, Benjamin Wong, Yan Stein, Lincoln Crosby, William Karlsson, Johan Royo, Romina Parraga, Ivan Ramirez, Sergio Gelpi, Josep Lluis Trelles, Oswaldo Pisano, David G Jimenez, Natalia Kerhornou, Arnaud Rosset, Roman Zamacola, Leire Tarraga, Joaquin Huerta-Cepas, Jaime Carazo, Jose Maria Dopazo, Joaquin Guigo, Roderic Navarro, Arcadi Orozco, Modesto Valencia, Alfonso Claros, M Gonzalo Perez, Antonio J Aldana, Jose Rojano, M Mar Fernandez-Santa Cruz, Raul Navas, Ismael Schiltz, Gary Farmer, Andrew Gessler, Damian Schoof, Heiko Groscurth, Andreas Research Support, Non-U.S. Gov’t Review England Briefings in bioinformatics Brief Bioinform. 2008 May;9(3):220-31. Epub 2008 Jan 31.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reumers, Joke</style></author><author><style face="normal" font="default" size="100%">Conde, Lucia</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Maurer-Stroh, Sebastian</style></author><author><style face="normal" font="default" size="100%">Van Durme, Joost</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Rousseau, Frederic</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, Joost</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Diseases, Inborn</style></keyword><keyword><style  face="normal" font="default" size="100%">HSP70 Heat-Shock Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Rats</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA Splice Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D825-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4,965,073 regulatory as well as 133,505 coding human SNPs and 14,935 disease mutations, and phenotypic descriptions of 43,797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Database issue</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/18086700?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reumers, J.</style></author><author><style face="normal" font="default" size="100%">L. Conde</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Maurer-Stroh, S.</style></author><author><style face="normal" font="default" size="100%">Van Durme, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Rousseau, F.</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution Animals *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Genetic Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Inborn/genetics HSP70 Heat-Shock Proteins/metabolism Humans Internet Mice MicroRNAs/metabolism *Mutation *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Proteins/chemistry/genetics RNA Splice Sites Rats Transcription Factors/metabolism</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://nar.oxfordjournals.org/cgi/content/full/36/suppl_1/D825</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">D825-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4,965,073 regulatory as well as 133,505 coding human SNPs and 14,935 disease mutations, and phenotypic descriptions of 43,797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Reumers, Joke Conde, Lucia Medina, Ignacio Maurer-Stroh, Sebastian Van Durme, Joost Dopazo, Joaquin Rousseau, Frederic Schymkowitz, Joost Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2008 Jan;36(Database issue):D825-9. Epub 2007 Dec 17.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Botton, A.</style></author><author><style face="normal" font="default" size="100%">Galla, G.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Bachem, C.</style></author><author><style face="normal" font="default" size="100%">Ramina, A.</style></author><author><style face="normal" font="default" size="100%">Barcaccia, G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-scale Gene Ontology analysis of plant transcriptome-derived sequences retrieved by AFLP technology</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=18652646</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">347</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;BACKGROUND: After 10-year-use of AFLP (Amplified Fragment Length Polymorphism) technology for DNA fingerprinting and mRNA profiling, large repertories of genome- and transcriptome-derived sequences are available in public databases for model, crop and tree species. AFLP marker systems have been and are being extensively exploited for genome scanning and gene mapping, as well as cDNA-AFLP for transcriptome profiling and differentially expressed gene cloning. The evaluation, annotation and classification of genomic markers and expressed transcripts would be of great utility for both functional genomics and systems biology research in plants. This may be achieved by means of the Gene Ontology (GO), consisting in three structured vocabularies (i.e. ontologies) describing genes, transcripts and proteins of any organism in terms of their associated cellular component, biological process and molecular function in a species-independent manner. In this paper, the functional annotation of about 8,000 AFLP-derived ESTs retrieved in the NCBI databases was carried out by using GO terminology. RESULTS: Descriptive statistics on the type, size and nature of gene sequences obtained by means of AFLP technology were calculated. The gene products associated with mRNA transcripts were then classified according to the three main GO vocabularies. A comparison of the functional content of cDNA-AFLP records was also performed by splitting the sequence dataset into monocots and dicots and by comparing them to all annotated ESTs of Arabidopsis and rice, respectively. On the whole, the statistical parameters adopted for the in silico AFLP-derived transcriptome-anchored sequence analysis proved to be critical for obtaining reliable GO results. Such an exhaustive annotation may offer a suitable platform for functional genomics, particularly useful in non-model species. CONCLUSION: Reliable GO annotations of AFLP-derived sequences can be gathered through the optimization of the experimental steps and the statistical parameters adopted. The Blast2GO software was shown to represent a comprehensive bioinformatics solution for an annotation-based functional analysis. According to the whole set of GO annotations, the AFLP technology generates thorough information for angiosperm gene products and shares common features across angiosperm species and families. The utility of this technology for structural and functional genomics in plants can be implemented by serial annotation analyses of genome-anchored fragments and organ/tissue-specific repertories of transcriptome-derived fragments.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Botton, Alessandro Galla, Giulio Conesa, Ana Bachem, Christian Ramina, Angelo Barcaccia, Gianni England BMC genomics BMC Genomics. 2008 Jul 24;9:347.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Martin-Campos, J. M.</style></author><author><style face="normal" font="default" size="100%">Lerma, E.</style></author><author><style face="normal" font="default" size="100%">Gimenez, G.</style></author><author><style face="normal" font="default" size="100%">Martinez-Guitarte, J. L.</style></author><author><style face="normal" font="default" size="100%">Combalia, N.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Matias-Guiu, X.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">de Leiva, A.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Mauricio, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information</style></title><secondary-title><style face="normal" font="default" size="100%">Oncogene</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adenoma/genetics/metabolism/pathology Adolescent Adult Aged Carcinoma/genetics/metabolism/pathology Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/*genetics/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm/genetics/metabolism Reverse Transcriptase Polymerase Chain Reaction Signal Transduction Thyroid Neoplasms/classification/*genetics/metabolism Tumor Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic Humans Male Middle Aged *Oligonucleotide Array Sequence Analysis Prognosis RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Papillary/genetics/metabolism/pathology Cell Differentiation Female *Gene Expression Profiling *Gene Expression Regulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17873908</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">1554-61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Undifferentiated and poorly differentiated thyroid tumors are responsible for more than half of thyroid cancer patient deaths in spite of their low incidence. Conventional treatments do not obtain substantial benefits, and the lack of alternative approaches limits patient survival. Additionally, the absence of prognostic markers for well-differentiated tumors complicates patient-specific treatments and favors the progression of recurrent forms. In order to recognize the molecular basis involved in tumor dedifferentiation and identify potential markers for thyroid cancer prognosis prediction, we analysed the expression profile of 44 thyroid primary tumors with different degrees of dedifferentiation and aggressiveness using cDNA microarrays. Transcriptome comparison of dedifferentiated and well-differentiated thyroid tumors identified 1031 genes with &amp;gt;2-fold difference in absolute values and false discovery rate of &amp;lt;0.15. According to known molecular interaction and reaction networks, the products of these genes were mainly clustered in the MAPkinase signaling pathway, the TGF-beta signaling pathway, focal adhesion and cell motility, activation of actin polymerization and cell cycle. An exhaustive search in several databases allowed us to identify various members of the matrix metalloproteinase, melanoma antigen A and collagen gene families within the upregulated gene set. We also identified a prognosis classifier comprising just 30 transcripts with an overall accuracy of 95%. These findings may clarify the molecular mechanisms involved in thyroid tumor dedifferentiation and provide a potential prognosis predictor as well as targets for new therapies.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Montero-Conde, C Martin-Campos, J M Lerma, E Gimenez, G Martinez-Guitarte, J L Combalia, N Montaner, D Matias-Guiu, X Dopazo, J de Leiva, A Robledo, M Mauricio, D Research Support, Non-U.S. Gov’t England Oncogene Oncogene. 2008 Mar 6;27(11):1554-61. Epub 2007 Sep 17.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Montero-Conde, C</style></author><author><style face="normal" font="default" size="100%">Martín-Campos, J M</style></author><author><style face="normal" font="default" size="100%">Lerma, E</style></author><author><style face="normal" font="default" size="100%">Gimenez, G</style></author><author><style face="normal" font="default" size="100%">Martínez-Guitarte, J L</style></author><author><style face="normal" font="default" size="100%">Combalía, N</style></author><author><style face="normal" font="default" size="100%">Montaner, D</style></author><author><style face="normal" font="default" size="100%">Matías-Guiu, X</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">de Leiva, A</style></author><author><style face="normal" font="default" size="100%">Robledo, M</style></author><author><style face="normal" font="default" size="100%">Mauricio, D</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information.</style></title><secondary-title><style face="normal" font="default" size="100%">Oncogene</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Oncogene</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adenoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Biomarkers, Tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Carcinoma, Papillary</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Reverse Transcriptase Polymerase Chain Reaction</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Thyroid Neoplasms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 Mar 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">1554-61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Undifferentiated and poorly differentiated thyroid tumors are responsible for more than half of thyroid cancer patient deaths in spite of their low incidence. Conventional treatments do not obtain substantial benefits, and the lack of alternative approaches limits patient survival. Additionally, the absence of prognostic markers for well-differentiated tumors complicates patient-specific treatments and favors the progression of recurrent forms. In order to recognize the molecular basis involved in tumor dedifferentiation and identify potential markers for thyroid cancer prognosis prediction, we analysed the expression profile of 44 thyroid primary tumors with different degrees of dedifferentiation and aggressiveness using cDNA microarrays. Transcriptome comparison of dedifferentiated and well-differentiated thyroid tumors identified 1031 genes with &gt;2-fold difference in absolute values and false discovery rate of &lt;0.15. According to known molecular interaction and reaction networks, the products of these genes were mainly clustered in the MAPkinase signaling pathway, the TGF-beta signaling pathway, focal adhesion and cell motility, activation of actin polymerization and cell cycle. An exhaustive search in several databases allowed us to identify various members of the matrix metalloproteinase, melanoma antigen A and collagen gene families within the upregulated gene set. We also identified a prognosis classifier comprising just 30 transcripts with an overall accuracy of 95%. These findings may clarify the molecular mechanisms involved in thyroid tumor dedifferentiation and provide a potential prognosis predictor as well as targets for new therapies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/17873908?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">K. Saar</style></author><author><style face="normal" font="default" size="100%">A. Beck</style></author><author><style face="normal" font="default" size="100%">M. T. Bihoreau</style></author><author><style face="normal" font="default" size="100%">E. Birney</style></author><author><style face="normal" font="default" size="100%">D. Brocklebank</style></author><author><style face="normal" font="default" size="100%">Y. Chen</style></author><author><style face="normal" font="default" size="100%">E. Cuppen</style></author><author><style face="normal" font="default" size="100%">S. Demonchy</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">P. Flicek</style></author><author><style face="normal" font="default" size="100%">M. Foglio</style></author><author><style face="normal" font="default" size="100%">A. Fujiyama</style></author><author><style face="normal" font="default" size="100%">I. G. Gut</style></author><author><style face="normal" font="default" size="100%">D. Gauguier</style></author><author><style face="normal" font="default" size="100%">R. Guigo</style></author><author><style face="normal" font="default" size="100%">V. Guryev</style></author><author><style face="normal" font="default" size="100%">M. Heinig</style></author><author><style face="normal" font="default" size="100%">O. Hummel</style></author><author><style face="normal" font="default" size="100%">N. Jahn</style></author><author><style face="normal" font="default" size="100%">S. Klages</style></author><author><style face="normal" font="default" size="100%">V. Kren</style></author><author><style face="normal" font="default" size="100%">M. Kube</style></author><author><style face="normal" font="default" size="100%">H. Kuhl</style></author><author><style face="normal" font="default" size="100%">Kuramoto, T.</style></author><author><style face="normal" font="default" size="100%">Kuroki, Y.</style></author><author><style face="normal" font="default" size="100%">Lechner, D.</style></author><author><style face="normal" font="default" size="100%">Lee, Y. A.</style></author><author><style face="normal" font="default" size="100%">Lopez-Bigas, N.</style></author><author><style face="normal" font="default" size="100%">Lathrop, G. M.</style></author><author><style face="normal" font="default" size="100%">Mashimo, T.</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Mott, R.</style></author><author><style face="normal" font="default" size="100%">Patone, G.</style></author><author><style face="normal" font="default" size="100%">Perrier-Cornet, J. A.</style></author><author><style face="normal" font="default" size="100%">Platzer, M.</style></author><author><style face="normal" font="default" size="100%">Pravenec, M.</style></author><author><style face="normal" font="default" size="100%">Reinhardt, R.</style></author><author><style face="normal" font="default" size="100%">Sakaki, Y.</style></author><author><style face="normal" font="default" size="100%">Schilhabel, M.</style></author><author><style face="normal" font="default" size="100%">Schulz, H.</style></author><author><style face="normal" font="default" size="100%">Serikawa, T.</style></author><author><style face="normal" font="default" size="100%">Shikhagaie, M.</style></author><author><style face="normal" font="default" size="100%">Tatsumoto, S.</style></author><author><style face="normal" font="default" size="100%">Taudien, S.</style></author><author><style face="normal" font="default" size="100%">Toyoda, A.</style></author><author><style face="normal" font="default" size="100%">Voigt, B.</style></author><author><style face="normal" font="default" size="100%">Zelenika, D.</style></author><author><style face="normal" font="default" size="100%">Zimdahl, H.</style></author><author><style face="normal" font="default" size="100%">Hubner, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SNP and haplotype mapping for genetic analysis in the rat</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals Chromosome Mapping *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Genome *Haplotypes Linkage Disequilibrium Phylogeny *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Inbred Strains/*genetics Recombination</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide *Quantitative Trait Loci Rats/*genetics Rats</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=18443594</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">560-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;STAR Consortium Saar, Kathrin Beck, Alfred Bihoreau, Marie-Therese Birney, Ewan Brocklebank, Denise Chen, Yuan Cuppen, Edwin Demonchy, Stephanie Dopazo, Joaquin Flicek, Paul Foglio, Mario Fujiyama, Asao Gut, Ivo G Gauguier, Dominique Guigo, Roderic Guryev, Victor Heinig, Matthias Hummel, Oliver Jahn, Niels Klages, Sven Kren, Vladimir Kube, Michael Kuhl, Heiner Kuramoto, Takashi Kuroki, Yoko Lechner, Doris Lee, Young-Ae Lopez-Bigas, Nuria Lathrop, G Mark Mashimo, Tomoji Medina, Ignacio Mott, Richard Patone, Giannino Perrier-Cornet, Jeanne-Antide Platzer, Matthias Pravenec, Michal Reinhardt, Richard Sakaki, Yoshiyuki Schilhabel, Markus Schulz, Herbert Serikawa, Tadao Shikhagaie, Medya Tatsumoto, Shouji Taudien, Stefan Toyoda, Atsushi Voigt, Birger Zelenika, Diana Zimdahl, Heike Hubner, Norbert 057733/Z/99/A/Wellcome Trust/United Kingdom 066780/Z/01/Z/Wellcome Trust/United Kingdom Research Support, Non-U.S. Gov’t Technical Report United States Nature genetics Nat Genet. 2008 May;40(5):560-6.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Saar, Kathrin</style></author><author><style face="normal" font="default" size="100%">Beck, Alfred</style></author><author><style face="normal" font="default" size="100%">Bihoreau, Marie-Thérèse</style></author><author><style face="normal" font="default" size="100%">Birney, Ewan</style></author><author><style face="normal" font="default" size="100%">Brocklebank, Denise</style></author><author><style face="normal" font="default" size="100%">Chen, Yuan</style></author><author><style face="normal" font="default" size="100%">Cuppen, Edwin</style></author><author><style face="normal" font="default" size="100%">Demonchy, Stephanie</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Flicek, Paul</style></author><author><style face="normal" font="default" size="100%">Foglio, Mario</style></author><author><style face="normal" font="default" size="100%">Fujiyama, Asao</style></author><author><style face="normal" font="default" size="100%">Gut, Ivo G</style></author><author><style face="normal" font="default" size="100%">Gauguier, Dominique</style></author><author><style face="normal" font="default" size="100%">Guigó, Roderic</style></author><author><style face="normal" font="default" size="100%">Guryev, Victor</style></author><author><style face="normal" font="default" size="100%">Heinig, Matthias</style></author><author><style face="normal" font="default" size="100%">Hummel, Oliver</style></author><author><style face="normal" font="default" size="100%">Jahn, Niels</style></author><author><style face="normal" font="default" size="100%">Klages, Sven</style></author><author><style face="normal" font="default" size="100%">Kren, Vladimir</style></author><author><style face="normal" font="default" size="100%">Kube, Michael</style></author><author><style face="normal" font="default" size="100%">Kuhl, Heiner</style></author><author><style face="normal" font="default" size="100%">Kuramoto, Takashi</style></author><author><style face="normal" font="default" size="100%">Kuroki, Yoko</style></author><author><style face="normal" font="default" size="100%">Lechner, Doris</style></author><author><style face="normal" font="default" size="100%">Lee, Young-Ae</style></author><author><style face="normal" font="default" size="100%">Lopez-Bigas, Nuria</style></author><author><style face="normal" font="default" size="100%">Lathrop, G Mark</style></author><author><style face="normal" font="default" size="100%">Mashimo, Tomoji</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Mott, Richard</style></author><author><style face="normal" font="default" size="100%">Patone, Giannino</style></author><author><style face="normal" font="default" size="100%">Perrier-Cornet, Jeanne-Antide</style></author><author><style face="normal" font="default" size="100%">Platzer, Matthias</style></author><author><style face="normal" font="default" size="100%">Pravenec, Michal</style></author><author><style face="normal" font="default" size="100%">Reinhardt, Richard</style></author><author><style face="normal" font="default" size="100%">Sakaki, Yoshiyuki</style></author><author><style face="normal" font="default" size="100%">Schilhabel, Markus</style></author><author><style face="normal" font="default" size="100%">Schulz, Herbert</style></author><author><style face="normal" font="default" size="100%">Serikawa, Tadao</style></author><author><style face="normal" font="default" size="100%">Shikhagaie, Medya</style></author><author><style face="normal" font="default" size="100%">Tatsumoto, Shouji</style></author><author><style face="normal" font="default" size="100%">Taudien, Stefan</style></author><author><style face="normal" font="default" size="100%">Toyoda, Atsushi</style></author><author><style face="normal" font="default" size="100%">Voigt, Birger</style></author><author><style face="normal" font="default" size="100%">Zelenika, Diana</style></author><author><style face="normal" font="default" size="100%">Zimdahl, Heike</style></author><author><style face="normal" font="default" size="100%">Hubner, Norbert</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">STAR Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">SNP and haplotype mapping for genetic analysis in the rat.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Linkage Disequilibrium</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Rats</style></keyword><keyword><style  face="normal" font="default" size="100%">Rats, Inbred Strains</style></keyword><keyword><style  face="normal" font="default" size="100%">Recombination, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">560-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/18443594?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Rossi, A.</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Davis, F. P.</style></author><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The AnnoLite and AnnoLyze programs for comparative annotation of protein structures</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Algorithms Amino Acid Sequence Confidence Intervals Data Interpretation</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid *Software Structure-Activity Relationship</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Information Storage and Retrieval/methods Molecular Sequence Data Proteins/*chemistry/classification/*metabolism Sensitivity and Specificity Sequence Alignment/*methods Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein/*methods Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical *Databases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17570147</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8 Suppl 4</style></volume><pages><style face="normal" font="default" size="100%">S4</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. DESCRIPTION: AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of  90% and average precision of  80%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of  70% and average precision of  30%, correctly localizing binding sites for small molecules in  95% of its predictions. CONCLUSION: The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.</style></abstract><notes><style face="normal" font="default" size="100%">Marti-Renom, Marc A Rossi, Andrea Al-Shahrour, Fatima Davis, Fred P Pieper, Ursula Dopazo, Joaquin Sali, Andrej Research Support, Non-U.S. Gov’t England BMC bioinformatics BMC Bioinformatics. 2007 May 22;8 Suppl 4:S4.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Milne, R. L.</style></author><author><style face="normal" font="default" size="100%">Moya, C. M.</style></author><author><style face="normal" font="default" size="100%">Cebrian, A.</style></author><author><style face="normal" font="default" size="100%">Leton, R.</style></author><author><style face="normal" font="default" size="100%">Cascon, A.</style></author><author><style face="normal" font="default" size="100%">Mercadillo, F.</style></author><author><style face="normal" font="default" size="100%">Landa, I.</style></author><author><style face="normal" font="default" size="100%">Borrego, S.</style></author><author><style face="normal" font="default" size="100%">Perez de Nanclares, G.</style></author><author><style face="normal" font="default" size="100%">Alvarez-Escola, C.</style></author><author><style face="normal" font="default" size="100%">Diaz-Perez, J. A.</style></author><author><style face="normal" font="default" size="100%">Carracedo, A.</style></author><author><style face="normal" font="default" size="100%">Urioste, M.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Neira, A.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author><author><style face="normal" font="default" size="100%">Santisteban, P.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Ponder, B. A.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma</style></title><secondary-title><style face="normal" font="default" size="100%">Cancer Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Proto-Oncogene Proteins c-ret/*genetics/metabolism Signal Transduction Thyroid Neoplasms/*genetics/metabolism Transcription</style></keyword><keyword><style  face="normal" font="default" size="100%">Medullary/*genetics/metabolism Case-Control Studies Cyclin-Dependent Kinase Inhibitor p15/biosynthesis/genetics Female Genetic Predisposition to Disease Germ-Line Mutation Haplotypes Humans Male Middle Aged Penetrance Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Promoter Regions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17909067</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">9561-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To date, few association studies have been done to better understand the genetic basis for the development of sporadic medullary thyroid carcinoma (sMTC). To identify additional low-penetrance genes, we have done a two-stage case-control study in two European populations using high-throughput genotyping. We selected 417 single nucleotide polymorphisms (SNP) belonging to 69 genes either related to RET signaling pathway/functions or involved in key processes for cancer development. TagSNPs and functional variants were included where possible. These SNPs were initially studied in the largest known series of sMTC cases (n = 266) and controls (n = 422), all of Spanish origin. In stage II, an independent British series of 155 sMTC patients and 531 controls was included to validate the previous results. Associations were assessed by an exhaustive analysis of individual SNPs but also considering gene- and linkage disequilibrium-based haplotypes. This strategy allowed us to identify seven low-penetrance genes, six of them (STAT1, AURKA, BCL2, CDKN2B, CDK6, and COMT) consistently associated with sMTC risk in the two case-control series and a seventh (HRAS) with individual SNPs and haplotypes associated with sMTC in the Spanish data set. The potential role of CDKN2B was confirmed by a functional assay showing a role of a SNP (rs7044859) in the promoter region in altering the binding of the transcription factor HNF1. These results highlight the utility of association studies using homogeneous series of cases for better understanding complex diseases.</style></abstract><notes><style face="normal" font="default" size="100%">Ruiz-Llorente, Sergio Montero-Conde, Cristina Milne, Roger L Moya, Christian M Cebrian, Arancha Leton, Rocio Cascon, Alberto Mercadillo, Fatima Landa, Inigo Borrego, Salud Perez de Nanclares, Guiomar Alvarez-Escola, Cristina Diaz-Perez, Jose Angel Carracedo, Angel Urioste, Miguel Gonzalez-Neira, Anna Benitez, Javier Santisteban, Pilar Dopazo, Joaquin Ponder, Bruce A Robledo, Mercedes Medullary Thyroid Carcinoma Clinical Group Research Support, Non-U.S. Gov’t United States Cancer research Cancer Res. 2007 Oct 1;67(19):9561-7.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marti-Renom, Marc A</style></author><author><style face="normal" font="default" size="100%">Pieper, Ursula</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M S</style></author><author><style face="normal" font="default" size="100%">Rossi, Andrea</style></author><author><style face="normal" font="default" size="100%">Eswar, Narayanan</style></author><author><style face="normal" font="default" size="100%">Davis, Fred P</style></author><author><style face="normal" font="default" size="100%">Al-Shahrour, Fátima</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Sali, Andrej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DBAli tools: mining the protein structure space.</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Interpretation, Statistical</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Data</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Conformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Pseudomonas aeruginosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Homology, Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Structure-Activity Relationship</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">W393-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The DBAli tools use a comprehensive set of structural alignments in the DBAli database to leverage the structural information deposited in the Protein Data Bank (PDB). These tools include (i) the DBAlit program that allows users to input the 3D coordinates of a protein structure for comparison by MAMMOTH against all chains in the PDB; (ii) the AnnoLite and AnnoLyze programs that annotate a target structure based on its stored relationships to other structures; (iii) the ModClus program that clusters structures by sequence and structure similarities; (iv) the ModDom program that identifies domains as recurrent structural fragments and (v) an implementation of the COMPARER method in the SALIGN command in MODELLER that creates a multiple structure alignment for a set of related protein structures. Thus, the DBAli tools, which are freely accessible via the World Wide Web at http://salilab.org/DBAli/, allow users to mine the protein structure space by establishing relationships between protein structures and their functions.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">Web Server issue</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/17478513?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Rossi, A.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Davis, F. P.</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DBAli tools: mining the protein structure space</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Algorithms Amino Acid Sequence Computational Biology/*methods Data Interpretation</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid *Software Structure-Activity Relationship</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Internet Molecular Sequence Data Protein Conformation Proteins/*chemistry/classification/*metabolism Pseudomonas aeruginosa/*metabolism Sequence Alignment/*methods Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein/*methods Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical *Databases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17478513</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">W393-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The DBAli tools use a comprehensive set of structural alignments in the DBAli database to leverage the structural information deposited in the Protein Data Bank (PDB). These tools include (i) the DBAlit program that allows users to input the 3D coordinates of a protein structure for comparison by MAMMOTH against all chains in the PDB; (ii) the AnnoLite and AnnoLyze programs that annotate a target structure based on its stored relationships to other structures; (iii) the ModClus program that clusters structures by sequence and structure similarities; (iv) the ModDom program that identifies domains as recurrent structural fragments and (v) an implementation of the COMPARER method in the SALIGN command in MODELLER that creates a multiple structure alignment for a set of related protein structures. Thus, the DBAli tools, which are freely accessible via the World Wide Web at http://salilab.org/DBAli/, allow users to mine the protein structure space by establishing relationships between protein structures and their functions.</style></abstract><notes><style face="normal" font="default" size="100%">Marti-Renom, Marc A Pieper, Ursula Madhusudhan, M S Rossi, Andrea Eswar, Narayanan Davis, Fred P Al-Shahrour, Fatima Dopazo, Joaquin Sali, Andrej GM 62529/GM/NIGMS NIH HHS/United States GM074929/GM/NIGMS NIH HHS/United States GM54762/GM/NIGMS NIH HHS/United States GM71790/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W393-7. Epub 2007 May 3.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">González-Neira, A</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">f single nucleotide polymorphism arrays: Design, tools and applications</style></title><secondary-title><style face="normal" font="default" size="100%">Microarray Technology Through Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis, F. Falciani</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rico, D.</style></author><author><style face="normal" font="default" size="100%">Vaquerizas, J. M.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Bosca, L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of conserved domains in the promoter regions of nitric oxide synthase 2: implications for the species-specific transcription and evolutionary differences</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals Base Sequence Conserved Sequence Enhancer Elements</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic *Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Response Elements Species Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Humans Inflammation/metabolism Interferon-gamma/metabolism Mice NF-kappa B/metabolism Nitric Oxide Synthase Type II/*genetics *Promoter Regions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17686182</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">271</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: The majority of the genes involved in the inflammatory response are highly conserved in mammals. These genes are not significantly expressed under normal conditions and are mainly regulated at the transcription and prost-transcriptional level. Transcription from the promoters of these genes is very dependent on NF-kappaB activation, which integrates the response to diverse extracellular stresses. However, in spite of the high conservation of the pattern of promoter regulation in kappaB-regulated genes, there is inter-species diversity in some genes. One example is nitric oxide synthase 2 (NOS-2), which exhibits a species-specific pattern of expression in response to infection or pro-inflammatory challenge. RESULTS: We have conducted a comparative genomic analysis of NOS-2 with different bioinformatic approaches. This analysis shows that in the NOS-2 gene promoter the position and the evolutionary divergence of some conserved regions are different in rodents and non-rodent mammals, and in particular in primates. Two not previously described distal regions in rodents that are similar to the unique upstream region responsible of the NF-kappaB activation of NOS-2 in humans are fragmented and translocated to different locations in the rodent promoters. The rodent sequences moreover lack the functional kappaB sites and IFN-gamma response sites present in the homologous human, rhesus monkey and chimpanzee regions. The absence of kappaB binding in these regions was confirmed by electrophoretic mobility shift assays. CONCLUSION: The data presented reveal divergence between rodents and other mammals in the location and functionality of conserved regions of the NOS-2 promoter containing NF-kappaB and IFN-gamma response elements.</style></abstract><notes><style face="normal" font="default" size="100%">Rico, Daniel Vaquerizas, Juan M Dopazo, Hernan Bosca, Lisardo Research Support, Non-U.S. Gov’t England BMC genomics BMC Genomics. 2007 Aug 8;8:271.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Schluter, A.</style></author><author><style face="normal" font="default" size="100%">Fourcade, S.</style></author><author><style face="normal" font="default" size="100%">Domenech-Estevez, E.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Berthommier, G.</style></author><author><style face="normal" font="default" size="100%">Ripp, R.</style></author><author><style face="normal" font="default" size="100%">Wanders, R. J.</style></author><author><style face="normal" font="default" size="100%">Poch, O.</style></author><author><style face="normal" font="default" size="100%">Pujol, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Genomics Humans Internet Mice Peroxisomal Disorders/*genetics Peroxisomes/*metabolism Protein Sorting Signals Proteome/chemistry/*genetics/*physiology Rats Saccharomyces cerevisiae Proteins/genetics/physiology Software User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17135190</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">D815-22</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Peroxisomes are essential organelles of eukaryotic origin, ubiquitously distributed in cells and organisms, playing key roles in lipid and antioxidant metabolism. Loss or malfunction of peroxisomes causes more than 20 fatal inherited conditions. We have created a peroxisomal database (http://www.peroxisomeDB.org) that includes the complete peroxisomal proteome of Homo sapiens and Saccharomyces cerevisiae, by gathering, updating and integrating the available genetic and functional information on peroxisomal genes. PeroxisomeDB is structured in interrelated sections ’Genes’, ’Functions’, ’Metabolic pathways’ and ’Diseases’, that include hyperlinks to selected features of NCBI, ENSEMBL and UCSC databases. We have designed graphical depictions of the main peroxisomal metabolic routes and have included updated flow charts for diagnosis. Precomputed BLAST, PSI-BLAST, multiple sequence alignment (MUSCLE) and phylogenetic trees are provided to assist in direct multispecies comparison to study evolutionary conserved functions and pathways. Highlights of the PeroxisomeDB include new tools developed for facilitating (i) identification of novel peroxisomal proteins, by means of identifying proteins carrying peroxisome targeting signal (PTS) motifs, (ii) detection of peroxisomes in silico, particularly useful for screening the deluge of newly sequenced genomes. PeroxisomeDB should contribute to the systematic characterization of the peroxisomal proteome and facilitate system biology approaches on the organelle.</style></abstract><notes><style face="normal" font="default" size="100%">Schluter, Agatha Fourcade, Stephane Domenech-Estevez, Enric Gabaldon, Toni Huerta-Cepas, Jaime Berthommier, Guillaume Ripp, Raymond Wanders, Ronald J A Poch, Olivier Pujol, Aurora Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2007 Jan;35(Database issue):D815-22. Epub 2006 Nov 28.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aparicio, G.</style></author><author><style face="normal" font="default" size="100%">Gotz, S.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Segrelles, D.</style></author><author><style face="normal" font="default" size="100%">Blanquer, I.</style></author><author><style face="normal" font="default" size="100%">Garcia, J. M.</style></author><author><style face="normal" font="default" size="100%">Hernandez, V.</style></author><author><style face="normal" font="default" size="100%">Robles, M.</style></author><author><style face="normal" font="default" size="100%">Talon, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Stud Health Technol Inform</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">babelomics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16823138</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">120</style></volume><pages><style face="normal" font="default" size="100%">194-204</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Aparicio, G Gotz, S Conesa, A Segrelles, D Blanquer, I Garcia, J M Hernandez, V Robles, M Talon, M Netherlands Studies in health technology and informatics Stud Health Technol Inform. 2006;120:194-204.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Milne, R. L.</style></author><author><style face="normal" font="default" size="100%">Ribas, G.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Neira, A.</style></author><author><style face="normal" font="default" size="100%">Fagerholm, R.</style></author><author><style face="normal" font="default" size="100%">Salas, A.</style></author><author><style face="normal" font="default" size="100%">Gonzalez, E.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Nevanlinna, H.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ERCC4 associated with breast cancer risk: a two-stage case-control study using high-throughput genotyping</style></title><secondary-title><style face="normal" font="default" size="100%">Cancer Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Breast Neoplasms/epidemiology/*genetics/pathology Case-Control Studies DNA-Binding Proteins/genetics/*physiology Female Finland/epidemiology Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Recessive Genetic Predisposition to Disease Genotype Humans Introns/genetics Linkage Disequilibrium Middle Aged Neoplasm Proteins/genetics/*physiology Neoplasm Staging *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Risk Spain/epidemiology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17018596</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">66</style></volume><pages><style face="normal" font="default" size="100%">9420-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The failure of linkage studies to identify further high-penetrance susceptibility genes for breast cancer points to a polygenic model, with more common variants having modest effects on risk, as the most likely candidate. We have carried out a two-stage case-control study in two European populations to identify low-penetrance genes for breast cancer using high-throughput genotyping. Single-nucleotide polymorphisms (SNPs) were selected across preselected cancer-related genes, choosing tagSNPs and functional variants where possible. In stage 1, genotype frequencies for 640 SNPs in 111 genes were compared between 864 breast cancer cases and 845 controls from the Spanish population. In stage 2, candidate SNPs identified in stage 1 (nominal P &lt; 0.01) were tested in a Finnish series of 884 cases and 1,104 controls. Of the 10 candidate SNPs in seven genes identified in stage 1, one (rs744154) on intron 1 of ERCC4, a gene belonging to the nucleotide excision repair pathway, was associated with recessive protection from breast cancer after adjustment for multiple testing in stage 2 (odds ratio, 0.57; Bonferroni-adjusted P = 0.04). After considering potential functional SNPs in the region of high linkage disequilibrium that extends across the entire gene and upstream into the promoter region, we concluded that rs744154 itself could be causal. Although intronic, it is located on the first intron, in a region that is highly conserved across species, and could therefore be functionally important. This study suggests that common intronic variation in ERCC4 is associated with protection from breast cancer.</style></abstract><notes><style face="normal" font="default" size="100%">Milne, Roger Laughlin Ribas, Gloria Gonzalez-Neira, Anna Fagerholm, Rainer Salas, Antonio Gonzalez, Emilio Dopazo, Joaquin Nevanlinna, Heli Robledo, Mercedes Benitez, Javier Comparative Study Multicenter Study Research Support, Non-U.S. Gov’t United States Cancer research Cancer Res. 2006 Oct 1;66(19):9420-7.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rossi, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Localization of binding sites in protein structures by optimization of a composite scoring function</style></title><secondary-title><style face="normal" font="default" size="100%">Protein Sci</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Binding Sites Biomechanics Hydrophobicity Ligands *Monte Carlo Method Protein Conformation Proteins/*chemistry Static Electricity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16963645</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">10</style></number><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">2366-80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The rise in the number of functionally uncharacterized protein structures is increasing the demand for structure-based methods for functional annotation. Here, we describe a method for predicting the location of a binding site of a given type on a target protein structure. The method begins by constructing a scoring function, followed by a Monte Carlo optimization, to find a good scoring patch on the protein surface. The scoring function is a weighted linear combination of the z-scores of various properties of protein structure and sequence, including amino acid residue conservation, compactness, protrusion, convexity, rigidity, hydrophobicity, and charge density; the weights are calculated from a set of previously identified instances of the binding-site type on known protein structures. The scoring function can easily incorporate different types of information useful in localization, thus increasing the applicability and accuracy of the approach. To test the method, 1008 known protein structures were split into 20 different groups according to the type of the bound ligand. For nonsugar ligands, such as various nucleotides, binding sites were correctly identified in 55%-73% of the cases. The method is completely automated (http://salilab.org/patcher) and can be applied on a large scale in a structural genomics setting.</style></abstract><notes><style face="normal" font="default" size="100%">Rossi, Andrea Marti-Renom, Marc A Sali, Andrej P01 AI035707/AI/NIAID NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t United States Protein science : a publication of the Protein Society Protein Sci. 2006 Oct;15(10):2366-80. Epub 2006 Sep 8.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Davis, F. P.</style></author><author><style face="normal" font="default" size="100%">Braberg, H.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Rossi, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Karchin, R.</style></author><author><style face="normal" font="default" size="100%">Webb, B. M.</style></author><author><style face="normal" font="default" size="100%">Eramian, D.</style></author><author><style face="normal" font="default" size="100%">Shen, M. Y.</style></author><author><style face="normal" font="default" size="100%">Kelly, L.</style></author><author><style face="normal" font="default" size="100%">Melo, F.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MODBASE: a database of annotated comparative protein structure models and associated resources</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding Sites *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Humans Internet Ligands *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Systems Integration User-Computer Interface</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Protein Structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Tertiary Proteins/*chemistry/genetics/metabolism Software *Structural Homology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16381869</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">D291-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models for all available protein sequences that can be matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, and improvements in the software for calculating the models. MODBASE currently contains 3 094 524 reliable models for domains in 1 094 750 out of 1 817 889 unique protein sequences in the UniProt database (July 5, 2005); only models based on statistically significant alignments and models assessed to have the correct fold despite insignificant alignments are included. MODBASE also allows users to generate comparative models for proteins of interest with the automated modeling server MODWEB (http://salilab.org/modweb). Our other resources integrated with MODBASE include comprehensive databases of multiple protein structure alignments (DBAli, http://salilab.org/dbali), structurally defined ligand binding sites and structurally defined binary domain interfaces (PIBASE, http://salilab.org/pibase) as well as predictions of ligand binding sites, interactions between yeast proteins, and functional consequences of human nsSNPs (LS-SNP, http://salilab.org/LS-SNP).</style></abstract><notes><style face="normal" font="default" size="100%">Pieper, Ursula Eswar, Narayanan Davis, Fred P Braberg, Hannes Madhusudhan, M S Rossi, Andrea Marti-Renom, Marc Karchin, Rachel Webb, Ben M Eramian, David Shen, Min-Yi Kelly, Libusha Melo, Francisco Sali, Andrej GM 08284/GM/NIGMS NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2006 Jan 1;34(Database issue):D291-5.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Conde</style></author><author><style face="normal" font="default" size="100%">Vaquerizas, J. M.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Reumers, J.</style></author><author><style face="normal" font="default" size="100%">Rousseau, F.</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms Computer Graphics Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genotype Haplotypes Internet Linkage Disequilibrium *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleic Acid Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide *Software User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://nar.oxfordjournals.org/cgi/content/full/34/suppl_2/W621</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">W621-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user’s data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Conde, Lucia Vaquerizas, Juan M Dopazo, Hernan Arbiza, Leonardo Reumers, Joke Rousseau, Frederic Schymkowitz, Joost Dopazo, Joaquin Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W621-5.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boxma, B.</style></author><author><style face="normal" font="default" size="100%">de Graaf, R. M.</style></author><author><style face="normal" font="default" size="100%">van der Staay, G. W.</style></author><author><style face="normal" font="default" size="100%">van Alen, T. A.</style></author><author><style face="normal" font="default" size="100%">Ricard, G.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">van Hoek, A. H.</style></author><author><style face="normal" font="default" size="100%">Moon-van der Staay, S. Y.</style></author><author><style face="normal" font="default" size="100%">Koopman, W. J.</style></author><author><style face="normal" font="default" size="100%">van Hellemond, J. J.</style></author><author><style face="normal" font="default" size="100%">Tielens, A. G.</style></author><author><style face="normal" font="default" size="100%">Friedrich, T.</style></author><author><style face="normal" font="default" size="100%">Veenhuis, M.</style></author><author><style face="normal" font="default" size="100%">M. A. Huynen</style></author><author><style face="normal" font="default" size="100%">Hackstein, J. H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An anaerobic mitochondrion that produces hydrogen</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Anaerobiosis Animals Ciliophora/*cytology/genetics/*metabolism/ultrastructure Cockroaches/parasitology DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial/genetics Electron Transport Electron Transport Complex I/antagonists &amp; inhibitors/metabolism Genome Glucose/metabolism Hydrogen/*metabolism Mitochondria/enzymology/genetics/*metabolism/ultrastructure Molecular Sequence Data Open Reading Fra</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15744302</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">7029</style></number><volume><style face="normal" font="default" size="100%">434</style></volume><pages><style face="normal" font="default" size="100%">74-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Hydrogenosomes are organelles that produce ATP and hydrogen, and are found in various unrelated eukaryotes, such as anaerobic flagellates, chytridiomycete fungi and ciliates. Although all of these organelles generate hydrogen, the hydrogenosomes from these organisms are structurally and metabolically quite different, just like mitochondria where large differences also exist. These differences have led to a continuing debate about the evolutionary origin of hydrogenosomes. Here we show that the hydrogenosomes of the anaerobic ciliate Nyctotherus ovalis, which thrives in the hindgut of cockroaches, have retained a rudimentary genome encoding components of a mitochondrial electron transport chain. Phylogenetic analyses reveal that those proteins cluster with their homologues from aerobic ciliates. In addition, several nucleus-encoded components of the mitochondrial proteome, such as pyruvate dehydrogenase and complex II, were identified. The N. ovalis hydrogenosome is sensitive to inhibitors of mitochondrial complex I and produces succinate as a major metabolic end product–biochemical traits typical of anaerobic mitochondria. The production of hydrogen, together with the presence of a genome encoding respiratory chain components, and biochemical features characteristic of anaerobic mitochondria, identify the N. ovalis organelle as a missing link between mitochondria and hydrogenosomes.</style></abstract><notes><style face="normal" font="default" size="100%">Boxma, Brigitte de Graaf, Rob M van der Staay, Georg W M van Alen, Theo A Ricard, Guenola Gabaldon, Toni van Hoek, Angela H A M Moon-van der Staay, Seung Yeo Koopman, Werner J H van Hellemond, Jaap J Tielens, Aloysius G M Friedrich, Thorsten Veenhuis, Marten Huynen, Martijn A Hackstein, Johannes H P Research Support, Non-U.S. Gov’t England Nature Nature. 2005 Mar 3;434(7029):74-9.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Gotz, S.</style></author><author><style face="normal" font="default" size="100%">Garcia-Gomez, J. M.</style></author><author><style face="normal" font="default" size="100%">Terol, J.</style></author><author><style face="normal" font="default" size="100%">Talon, M.</style></author><author><style face="normal" font="default" size="100%">Robles, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">babelomics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16081474</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">18</style></number><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">3674-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. AVAILABILITY: Blast2GO is freely available via Java Web Start at http://www.blast2go.de. SUPPLEMENTARY MATERIAL: http://www.blast2go.de -&amp;gt; Evaluation.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Conesa, Ana Gotz, Stefan Garcia-Gomez, Juan Miguel Terol, Javier Talon, Manuel Robles, Montserrat Research Support, Non-U.S. Gov’t England Bioinformatics (Oxford, England) Bioinformatics. 2005 Sep 15;21(18):3674-6. Epub 2005 Aug 4.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">J. Forment</style></author><author><style face="normal" font="default" size="100%">J. Gadea</style></author><author><style face="normal" font="default" size="100%">Huerta, L.</style></author><author><style face="normal" font="default" size="100%">Abizanda, L.</style></author><author><style face="normal" font="default" size="100%">Agusti, J.</style></author><author><style face="normal" font="default" size="100%">Alamar, S.</style></author><author><style face="normal" font="default" size="100%">Alos, E.</style></author><author><style face="normal" font="default" size="100%">Andres, F.</style></author><author><style face="normal" font="default" size="100%">Arribas, R.</style></author><author><style face="normal" font="default" size="100%">Beltran, J. P.</style></author><author><style face="normal" font="default" size="100%">Berbel, A.</style></author><author><style face="normal" font="default" size="100%">Blazquez, M. A.</style></author><author><style face="normal" font="default" size="100%">Brumos, J.</style></author><author><style face="normal" font="default" size="100%">Canas, L. A.</style></author><author><style face="normal" font="default" size="100%">Cercos, M.</style></author><author><style face="normal" font="default" size="100%">Colmenero-Flores, J. M.</style></author><author><style face="normal" font="default" size="100%">A. Conesa</style></author><author><style face="normal" font="default" size="100%">Estables, B.</style></author><author><style face="normal" font="default" size="100%">Gandia, M.</style></author><author><style face="normal" font="default" size="100%">Garcia-Martinez, J. L.</style></author><author><style face="normal" font="default" size="100%">Gimeno, J.</style></author><author><style face="normal" font="default" size="100%">Gisbert, A.</style></author><author><style face="normal" font="default" size="100%">Gomez, G.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Candelas, L.</style></author><author><style face="normal" font="default" size="100%">Granell, A.</style></author><author><style face="normal" font="default" size="100%">Guerri, J.</style></author><author><style face="normal" font="default" size="100%">Lafuente, M. T.</style></author><author><style face="normal" font="default" size="100%">Madueno, F.</style></author><author><style face="normal" font="default" size="100%">Marcos, J. F.</style></author><author><style face="normal" font="default" size="100%">Marques, M. C.</style></author><author><style face="normal" font="default" size="100%">Martinez, F.</style></author><author><style face="normal" font="default" size="100%">Martinez-Godoy, M. A.</style></author><author><style face="normal" font="default" size="100%">Miralles, S.</style></author><author><style face="normal" font="default" size="100%">Moreno, P.</style></author><author><style face="normal" font="default" size="100%">Navarro, L.</style></author><author><style face="normal" font="default" size="100%">Pallas, V.</style></author><author><style face="normal" font="default" size="100%">Perez-Amador, M. A.</style></author><author><style face="normal" font="default" size="100%">Perez-Valle, J.</style></author><author><style face="normal" font="default" size="100%">Pons, C.</style></author><author><style face="normal" font="default" size="100%">Rodrigo, I.</style></author><author><style face="normal" font="default" size="100%">Rodriguez, P. L.</style></author><author><style face="normal" font="default" size="100%">Royo, C.</style></author><author><style face="normal" font="default" size="100%">Serrano, R.</style></author><author><style face="normal" font="default" size="100%">Soler, G.</style></author><author><style face="normal" font="default" size="100%">Tadeo, F.</style></author><author><style face="normal" font="default" size="100%">Talon, M.</style></author><author><style face="normal" font="default" size="100%">Terol, J.</style></author><author><style face="normal" font="default" size="100%">Trenor, M.</style></author><author><style face="normal" font="default" size="100%">Vaello, L.</style></author><author><style face="normal" font="default" size="100%">Vicente, O.</style></author><author><style face="normal" font="default" size="100%">Vidal, Ch</style></author><author><style face="normal" font="default" size="100%">Zacarias, L.</style></author><author><style face="normal" font="default" size="100%">Conejero, V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of a citrus genome-wide EST collection and cDNA microarray as resources for genomic studies</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Citrus/*genetics DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Complementary/chemistry/genetics *Expressed Sequence Tags Gene Expression Profiling Gene Library *Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Genomics/*methods Molecular Sequence Data Oligonucleotide Array Sequence Analysis/*methods RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant/genetics/metabolism Reproducibility of Results Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15830128</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">375-91</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A functional genomics project has been initiated to approach the molecular characterization of the main biological and agronomical traits of citrus. As a key part of this project, a citrus EST collection has been generated from 25 cDNA libraries covering different tissues, developmental stages and stress conditions. The collection includes a total of 22,635 high-quality ESTs, grouped in 11,836 putative unigenes, which represent at least one third of the estimated number of genes in the citrus genome. Functional annotation of unigenes which have Arabidopsis orthologues (68% of all unigenes) revealed gene representation in every major functional category, suggesting that a genome-wide EST collection was obtained. A Citrus clementina Hort. ex Tan. cv. Clemenules genomic library, that will contribute to further characterization of relevant genes, has also been constructed. To initiate the analysis of citrus transcriptome, we have developed a cDNA microarray containing 12,672 probes corresponding to 6875 putative unigenes of the collection. Technical characterization of the microarray showed high intra- and inter-array reproducibility, as well as a good range of sensitivity. We have also validated gene expression data achieved with this microarray through an independent technique such as RNA gel blot analysis.</style></abstract><notes><style face="normal" font="default" size="100%">Forment, J Gadea, J Huerta, L Abizanda, L Agusti, J Alamar, S Alos, E Andres, F Arribas, R Beltran, J P Berbel, A Blazquez, M A Brumos, J Canas, L A Cercos, M Colmenero-Flores, J M Conesa, A Estables, B Gandia, M Garcia-Martinez, J L Gimeno, J Gisbert, A Gomez, G Gonzalez-Candelas, L Granell, A Guerri, J Lafuente, M T Madueno, F Marcos, J F Marques, M C Martinez, F Martinez-Godoy, M A Miralles, S Moreno, P Navarro, L Pallas, V Perez-Amador, M A Perez-Valle, J Pons, C Rodrigo, I Rodriguez, P L Royo, C Serrano, R Soler, G Tadeo, F Talon, M Terol, J Trenor, M Vaello, L Vicente, O Vidal, Ch Zacarias, L Conejero, V Comparative Study Research Support, U.S. Gov’t, Non-P.H.S. Netherlands Plant molecular biology Plant Mol Biol. 2005 Feb;57(3):375-91.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cascon, A.</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Perales, S.</style></author><author><style face="normal" font="default" size="100%">Honrado, E.</style></author><author><style face="normal" font="default" size="100%">Martinez-Ramirez, A.</style></author><author><style face="normal" font="default" size="100%">Leton, R.</style></author><author><style face="normal" font="default" size="100%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel candidate region linked to development of both pheochromocytoma and head/neck paraganglioma</style></title><secondary-title><style face="normal" font="default" size="100%">Genes Chromosomes Cancer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Child Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent Adrenal Gland Neoplasms/*genetics Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/*genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 1/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 11/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 3/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 8/genetics Female Gene Deletion Head and Neck Neoplasms/*genetics Humans Male Middle Aged Nucleic Acid Hybridization Paraganglioma/*genetics Pheochromocytoma/*genetics Tumor Markers</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15609347</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">260-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Although the histologic distinction between pheochromocytomas and head and neck paragangliomas is clear, little is known about the genetic differences between them. To date, various sets of genes have been found to be involved in inherited susceptibility to developing both tumor types, but the genes involved in sporadic pathogenesis are still unknown. To define new candidate regions, we performed CGH analysis on 29 pheochromocytomas and on 24 paragangliomas mainly of head and neck origin (20 of 24), which allowed us to differentiate between the two tumor types. Loss of 3q was significantly more frequent in pheochromocytomas, and loss of 1q appeared only in paragangliomas. We also found gain of 11q13 to be a significantly frequent alteration in malignant cases of both types. In addition, recurrent loss of 8p22-23 was found in 62% of pheochromocytomas (including all malignant cases) versus in 33% of paragangliomas, suggesting that this region contains candidate genes involved in the pathogenesis of this abnormality. Using FISH analysis on tissue microarrays, we confirmed genomic deletion of this region in 55% of pheochromocytomas compared to 12% of paragangliomas. Loss of 8p22-23 appears to be an important event in the sporadic development of these tumors, and additional molecular studies are necessary to identify candidate genes in this chromosomal region.</style></abstract><notes><style face="normal" font="default" size="100%">Cascon, Alberto Ruiz-Llorente, Sergio Rodriguez-Perales, Sandra Honrado, Emiliano Martinez-Ramirez, Angel Leton, Rocio Montero-Conde, Cristina Benitez, Javier Dopazo, Joaquin Cigudosa, Juan C Robledo, Mercedes Research Support, Non-U.S. Gov’t United States Genes, chromosomes &amp; cancer Genes Chromosomes Cancer. 2005 Mar;42(3):260-8.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Palacios, J.</style></author><author><style face="normal" font="default" size="100%">Honrado, E.</style></author><author><style face="normal" font="default" size="100%">Osorio, A.</style></author><author><style face="normal" font="default" size="100%">Cazorla, A.</style></author><author><style face="normal" font="default" size="100%">Sarrio, D.</style></author><author><style face="normal" font="default" size="100%">Barroso, A.</style></author><author><style face="normal" font="default" size="100%">Rodriguez, S.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">Diez, O.</style></author><author><style face="normal" font="default" size="100%">Alonso, C.</style></author><author><style face="normal" font="default" size="100%">Lerma, E.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Rivas, C.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phenotypic characterization of BRCA1 and BRCA2 tumors based in a tissue microarray study with 37 immunohistochemical markers</style></title><secondary-title><style face="normal" font="default" size="100%">Breast Cancer Res Treat</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult Apoptosis Breast Neoplasms/*genetics/*pathology Cell Cycle Proteins Cluster Analysis Female *Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/genetics/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">BRCA1 *Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">BRCA2 Humans Immunohistochemistry In Situ Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">Fluorescence Phenotype Spain *Tissue Array Analysis *Tumor Markers</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15770521</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">90</style></volume><pages><style face="normal" font="default" size="100%">5-14</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Familial breast cancers that are associated with BRCA1 or BRCA2 germline mutations differ in both their morphological and immunohistochemical characteristics. To further characterize the molecular difference between genotypes, the authors evaluated the expression of 37 immunohistochemical markers in a tissue microarray (TMA) containing cores from 20 BRCA1, 14 BRCA2, and 59 sporadic age-matched breast carcinomas. Markers analyzed included, amog others, common markers in breast cancer, such as hormone receptors, p53 and HER2, along with 15 molecules involved in cell cycle regulation, such as cyclins, cyclin dependent kinases (CDK) and CDK inhibitors (CDKI), apoptosis markers, such as BCL2 and active caspase 3, and two basal/myoepithelial markers (CK 5/6 and P-cadherin). In addition, we analyzed the amplification of CCND1, CCNE, HER2 and MYC by FISH.Unsupervised cluster data analysis of both hereditary and sporadic cases using the complete set of immunohistochemical markers demonstrated that most BRCA1-associated carcinomas grouped in a branch of ER-, HER2-negative tumors that expressed basal cell markers and/or p53 and had higher expression of activated caspase 3. The cell cycle proteins associated with these tumors were E2F6, cyclins A, B1 and E, SKP2 and Topo IIalpha. In contrast, most BRCA2-associated carcinomas grouped in a branch composed by ER/PR/BCL2-positive tumors with a higher expression of the cell cycle proteins cyclin D1, cyclin D3, p27, p16, p21, CDK4, CDK2 and CDK1. In conclusion, our study in hereditary breast cancer tumors analyzing 37 immunohistochemical markers, define the molecular differences between BRCA1 and BRCA2 tumors with respect to hormonal receptors, cell cycle, apoptosis and basal cell markers.</style></abstract><notes><style face="normal" font="default" size="100%">Palacios, Jose Honrado, Emiliano Osorio, Ana Cazorla, Alicia Sarrio, David Barroso, Alicia Rodriguez, Sandra Cigudosa, Juan C Diez, Orland Alonso, Carmen Lerma, Enrique Dopazo, Joaquin Rivas, Carmen Benitez, Javier Research Support, Non-U.S. Gov’t Netherlands Breast cancer research and treatment Breast Cancer Res Treat. 2005 Mar;90(1):5-14.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alvarez, S.</style></author><author><style face="normal" font="default" size="100%">Diaz-Uriarte, R.</style></author><author><style face="normal" font="default" size="100%">Osorio, A.</style></author><author><style face="normal" font="default" size="100%">Barroso, A.</style></author><author><style face="normal" font="default" size="100%">Melchor, L.</style></author><author><style face="normal" font="default" size="100%">Paz, M. F.</style></author><author><style face="normal" font="default" size="100%">Honrado, E.</style></author><author><style face="normal" font="default" size="100%">Rodriguez, R.</style></author><author><style face="normal" font="default" size="100%">Urioste, M.</style></author><author><style face="normal" font="default" size="100%">Valle, L.</style></author><author><style face="normal" font="default" size="100%">Diez, O.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Esteller, M.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A predictor based on the somatic genomic changes of the BRCA1/BRCA2 breast cancer tumors identifies the non-BRCA1/BRCA2 tumors with BRCA1 promoter hypermethylation</style></title><secondary-title><style face="normal" font="default" size="100%">Clin Cancer Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">BRCA1 Protein/*genetics BRCA2 Protein/*genetics Breast Neoplasms/*genetics/pathology Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic/*genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Humans Male Mutation Nucleic Acid Hybridization/methods Promoter Regions</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 12/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 15/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 18/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 2/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 8/genetics *DNA Methylation Female Genome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15709182</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1146-53</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The genetic changes underlying in the development and progression of familial breast cancer are poorly understood. To identify a somatic genetic signature of tumor progression for each familial group, BRCA1, BRCA2, and non-BRCA1/BRCA2 (BRCAX) tumors, by high-resolution comparative genomic hybridization, we have analyzed 77 tumors previously characterized for BRCA1 and BRCA2 germ line mutations. Based on a combination of the somatic genetic changes observed at the six most different chromosomal regions and the status of the estrogen receptor, we developed using random forests a molecular classifier, which assigns to a given tumor a probability to belong either to the BRCA1 or to the BRCA2 class. Because 76.5% (26 of 34) of the BRCAX cases were classified with our predictor to the BRCA1 class with a probability of &gt;50%, we analyzed the BRCA1 promoter region for aberrant methylation in all the BRCAX cases. We found that 15 of the 34 BRCAX analyzed tumors had hypermethylation of the BRCA1 gene. When we considered the predictor, we observed that all the cases with this epigenetic event were assigned to the BRCA1 class with a probability of &gt;50%. Interestingly, 84.6% of the cases (11 of 13) assigned to the BRCA1 class with a probability &gt;80% had an aberrant methylation of the BRCA1 promoter. This fact suggests that somatic BRCA1 inactivation could modify the profile of tumor progression in most of the BRCAX cases.</style></abstract><notes><style face="normal" font="default" size="100%">Alvarez, Sara Diaz-Uriarte, Ramon Osorio, Ana Barroso, Alicia Melchor, Lorenzo Paz, Maria Fe Honrado, Emiliano Rodriguez, Raquel Urioste, Miguel Valle, Laura Diez, Orland Cigudosa, Juan Cruz Dopazo, Joaquin Esteller, Manel Benitez, Javier Comparative Study Research Support, Non-U.S. Gov’t United States Clinical cancer research : an official journal of the American Association for Cancer Research Clin Cancer Res. 2005 Feb 1;11(3):1146-53.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antón, J</style></author><author><style face="normal" font="default" size="100%">Peña, A</style></author><author><style face="normal" font="default" size="100%">Valens, M</style></author><author><style face="normal" font="default" size="100%">Santos, F</style></author><author><style face="normal" font="default" size="100%">Glöckner, F.O</style></author><author><style face="normal" font="default" size="100%">Bauer, M</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Herrero, J.</style></author><author><style face="normal" font="default" size="100%">Rosselló-Mora, R</style></author><author><style face="normal" font="default" size="100%">Amann, R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Salinibacter ruber: genomics and biogeography</style></title><secondary-title><style face="normal" font="default" size="100%">Adaptation to life in high salt concentrations in Archaea, Bacteria and Eukarya</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">Nina Gunde-Cimerman, Ana Plemenitas, and Aharon Oren. Kluwer Academic Publishers</style></publisher><pub-location><style face="normal" font="default" size="100%">Dordrecht, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">257-266</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Rainey, D.</style></author><author><style face="normal" font="default" size="100%">M. A. Huynen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tracing the evolution of a large protein complex in the eukaryotes, NADH:ubiquinone oxidoreductase (Complex I)</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Animals Computational Biology Electron Transport Complex I/*chemistry/*genetics/metabolism Eukaryotic Cells/*enzymology *Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Humans Molecular Sequence Data Photosynthesis Phylogeny Plastids/enzymology Protein Binding Protein Subunits/chemistry/genetics/metabolism Sequence Alignment Structural Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15843018</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">348</style></volume><pages><style face="normal" font="default" size="100%">857-70</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The increasing availability of sequenced genomes enables the reconstruction of the evolutionary history of large protein complexes. Here, we trace the evolution of NADH:ubiquinone oxidoreductase (Complex I), which has increased in size, by so-called supernumary subunits, from 14 subunits in the bacteria to 30 in the plants and algae, 37 in the fungi and 46 in the mammals. Using a combination of pair-wise and profile-based sequence comparisons at the levels of proteins and the DNA of the sequenced eukaryotic genomes, combined with phylogenetic analyses to establish orthology relationships, we were able to (1) trace the origin of six of the supernumerary subunits to the alpha-proteobacterial ancestor of the mitochondria, (2) detect previously unidentified homology relations between subunits from fungi and mammals, (3) detect previously unidentified subunits in the genomes of several species and (4) document several cases of gene duplications among supernumerary subunits in the eukaryotes. One of these, a duplication of N7BM (B17.2), is particularly interesting as it has been lost from genomes that have also lost Complex I proteins, making it a candidate for a Complex I interacting protein. A parsimonious reconstruction of eukaryotic Complex I evolution shows an initial increase in size that predates the separation of plants, fungi and metazoa, followed by a gradual adding and incidental losses of subunits in the various evolutionary lineages. This evolutionary scenario is in contrast to that for Complex I in the prokaryotes, for which the combination of several separate, and previously independently functioning modules into a single complex has been proposed.</style></abstract><notes><style face="normal" font="default" size="100%">Gabaldon, Toni Rainey, Daphne Huynen, Martijn A Research Support, Non-U.S. Gov’t England Journal of molecular biology J Mol Biol. 2005 May 13;348(4):857-70.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martinez-Delgado, Beatriz</style></author><author><style face="normal" font="default" size="100%">Meléndez, Barbara</style></author><author><style face="normal" font="default" size="100%">Cuadros, Marta</style></author><author><style face="normal" font="default" size="100%">Alvarez, Javier</style></author><author><style face="normal" font="default" size="100%">Castrillo, Jose Maria</style></author><author><style face="normal" font="default" size="100%">Ruiz De La Parte, Ana</style></author><author><style face="normal" font="default" size="100%">Mollejo, Manuela</style></author><author><style face="normal" font="default" size="100%">Bellas, Carmen</style></author><author><style face="normal" font="default" size="100%">Diaz, Ramon</style></author><author><style face="normal" font="default" size="100%">Lombardía, Luis</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Domínguez, Orlando</style></author><author><style face="normal" font="default" size="100%">Cascon, Alberto</style></author><author><style face="normal" font="default" size="100%">Robledo, Mercedes</style></author><author><style face="normal" font="default" size="100%">Rivas, Carmen</style></author><author><style face="normal" font="default" size="100%">Benitez, Javier</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expression profiling of T-cell lymphomas differentiates peripheral and lymphoblastic lymphomas and defines survival related genes.</style></title><secondary-title><style face="normal" font="default" size="100%">Clinical cancer research : an official journal of the American Association for Cancer Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2004 Aug 1</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://clincancerres.aacrjournals.org/content/10/15/4971.long</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">4971-82</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;PURPOSE: T-Cell lymphomas constitute heterogeneous and aggressive tumors in which pathogenic alterations remain largely unknown. Expression profiling has demonstrated to be a useful tool for molecular classification of tumors. EXPERIMENTAL DESIGN: Using DNA microarrays (CNIO-OncoChip) containing 6386 cancer-related genes, we established the expression profiling of T-cell lymphomas and compared them to normal lymphocytes and lymph nodes. RESULTS: We found significant differences between the peripheral and lymphoblastic T-cell lymphomas, which include a deregulation of nuclear factor-kappaB signaling pathway. We also identify differentially expressed genes between peripheral T-cell lymphoma tumors and normal T lymphocytes or reactive lymph nodes, which could represent candidate tumor markers of these lymphomas. Additionally, a close relationship between genes associated to survival and those that differentiate among the stages of disease and responses to therapy was found. CONCLUSIONS: Our results reflect the value of gene expression profiling to gain insight about the molecular alterations involved in the pathogenesis of T-cell lymphomas.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Melendez, B.</style></author><author><style face="normal" font="default" size="100%">Diaz-Uriarte, R.</style></author><author><style face="normal" font="default" size="100%">Cuadros, M.</style></author><author><style face="normal" font="default" size="100%">Martinez-Ramirez, A.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Piqueras, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, A.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">Rivas, C.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Martinez-Delgado, B.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gene expression analysis of chromosomal regions with gain or loss of genetic material detected by comparative genomic hybridization</style></title><secondary-title><style face="normal" font="default" size="100%">Genes Chromosomes Cancer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Fluorescence Lymphoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 13/*genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 19/*genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 6/*genetics Expressed Sequence Tags *Gene Dosage Gene Expression Profiling Humans In Situ Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">T-Cell/*genetics Nucleic Acid Hybridization Oligonucleotide Array Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15382261</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">353-65</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Comparative genomic hybridization (CGH) has been widely used to detect copy number alterations in cancer and to identify regions containing candidate tumor-responsible genes; however, gene expression changes have been described only in highly amplified regions (amplicons). To study the overall impact of slight copy number changes on gene expression, we analyzed 16 T-cell lymphomas by using CGH and a custom-designed cDNA microarray containing 7,657 genes and expressed sequence tags related to tumorigenesis. We evaluated mean gene expression and variability within CGH-altered regions and explored the relationship between the effects of the gene and its position within these regions. Minimally overlapping CGH candidate areas (6q25, 13q21-q22, and 19q13.1) revealed a weak relationship between altered genomic content and gene expression. However, some candidate genes showed modified expression within these regions in the majority of tumors; these candidate genes were evaluated and confirmed in another independent series of 23 T-cell lymphomas by use of the same cDNA microarray and by FISH on a tissue microarray. When all the CGH regions detected for each tumor were considered, we found a significant increase or decrease in the mean expression of the genes contained in gained or lost regions, respectively. In addition, we found that the expression of a gene was dependent not only on its position within an altered region but also on its own mechanism of regulation: genes in the same altered region responded very differently to the gain or loss of genetic material. Supplementary material for this article can be found on the Genes, Chromosomes, and Cancer website at http://www.interscience.wiley.com/jpages/1045-2257/suppmat/index.html.</style></abstract><notes><style face="normal" font="default" size="100%">Melendez, Barbara Diaz-Uriarte, Ramon Cuadros, Marta Martinez-Ramirez, Angel Fernandez-Piqueras, Jose Dopazo, Ana Cigudosa, Juan-Cruz Rivas, Carmen Dopazo, Joaquin Martinez-Delgado, Beatriz Benitez, Javier Research Support, Non-U.S. Gov’t United States Genes, chromosomes &amp; cancer Genes Chromosomes Cancer. 2004 Dec;41(4):353-65.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pieper, U.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Braberg, H.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Davis, F. P.</style></author><author><style face="normal" font="default" size="100%">Stuart, A. C.</style></author><author><style face="normal" font="default" size="100%">Mirkovic, N.</style></author><author><style face="normal" font="default" size="100%">Rossi, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Webb, B.</style></author><author><style face="normal" font="default" size="100%">Greenblatt, D.</style></author><author><style face="normal" font="default" size="100%">Huang, C. C.</style></author><author><style face="normal" font="default" size="100%">Ferrin, T. E.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MODBASE, a database of annotated comparative protein structure models, and associated resources</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Animals Binding Sites *Computational Biology *Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Molecular Sequence Data Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Genomics Humans Internet Ligands Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Protein Binding Protein Conformation Proteins/*chemistry/genetics Sequence Alignment Software User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=14681398</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Database issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">D217-22</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">MODBASE (http://salilab.org/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on the MODELLER package for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE uses the MySQL relational database management system for flexible querying and CHIMERA for viewing the sequences and structures (http://www.cgl.ucsf.edu/chimera/). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different data sets. The largest data set contains 1,26,629 models for domains in 659,495 out of 1,182,126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only models based on alignments with significant similarity scores and models assessed to have the correct fold despite insignificant alignments are included. Another model data set supports target selection and structure-based annotation by the New York Structural Genomics Research Consortium; e.g. the 53 new structures produced by the consortium allowed us to characterize structurally 24,113 sequences. MODBASE also contains binding site predictions for small ligands and a set of predicted interactions between pairs of modeled sequences from the same genome. Our other resources associated with MODBASE include a comprehensive database of multiple protein structure alignments (DBALI, http://salilab.org/dbali) as well as web servers for automated comparative modeling with MODPIPE (MODWEB, http://salilab. org/modweb), modeling of loops in protein structures (MODLOOP, http://salilab.org/modloop) and predicting functional consequences of single nucleotide polymorphisms (SNPWEB, http://salilab. org/snpweb).</style></abstract><notes><style face="normal" font="default" size="100%">Pieper, Ursula Eswar, Narayanan Braberg, Hannes Madhusudhan, M S Davis, Fred P Stuart, Ashley C Mirkovic, Nebojsa Rossi, Andrea Marti-Renom, Marc A Fiser, Andras Webb, Ben Greenblatt, Daniel Huang, Conrad C Ferrin, Thomas E Sali, Andrej P41 RR01081/RR/NCRR NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM 54762/GM/NIGMS NIH HHS/United States R33 CA84699/CA/NCI NIH HHS/United States Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2004 Jan 1;32(Database issue):D217-22.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Conde</style></author><author><style face="normal" font="default" size="100%">Vaquerizas, J. M.</style></author><author><style face="normal" font="default" size="100%">J. Santoyo</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PupaSNP Finder: a web tool for finding SNPs with putative effect at transcriptional level</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution Binding Sites Humans Internet Phenotype *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide RNA Splicing *Software Transcription Factors/metabolism *Transcription</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15215388</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">W242-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have developed a web tool, PupaSNP Finder (PupaSNP for short), for high-throughput searching for single nucleotide polymorphisms (SNPs) with potential phenotypic effect. PupaSNP takes as its input lists of genes (or generates them from chromosomal coordinates) and retrieves SNPs that could affect the conserved regions that the cellular machinery uses for the correct processing of genes (intron/exon boundaries or exonic splicing enhancers), predicted transcription factor binding sites (TFBS) and changes in amino acids in the proteins. The program uses the mapping of SNPs in the genome provided by Ensembl. Additionally, user-defined SNPs (not yet mapped in the genome) can be easily provided to the program. Also, additional functional information from Gene Ontology, OMIM and homologies in other model organisms is provided. In contrast to other programs already available, which focus only on SNPs with possible effect in the protein, PupaSNP includes SNPs with possible transcriptional effect. PupaSNP will be of significant help in studies of multifactorial disorders, where the use of functional SNPs will increase the sensitivity of identification of the genes responsible for the disease. The PupaSNP web interface is accessible through http://pupasnp.bioinfo.cnio.es.</style></abstract><notes><style face="normal" font="default" size="100%">Conde, Lucia Vaquerizas, Juan M Santoyo, Javier Al-Shahrour, Fatima Ruiz-Llorente, Sergio Robledo, Mercedes Dopazo, Joaquin England Nucleic acids research Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W242-8.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koh, I. Y.</style></author><author><style face="normal" font="default" size="100%">Eyrich, V. A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Przybylski, D.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Grana, O.</style></author><author><style face="normal" font="default" size="100%">Pazos, F.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EVA: Evaluation of protein structure prediction servers</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automation Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Internet *Protein Conformation Protein Folding Protein Structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Structural Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Secondary Proteins/chemistry Reproducibility of Results *Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12824315</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">13</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">3311-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">EVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.</style></abstract><notes><style face="normal" font="default" size="100%">Koh, Ingrid Y Y Eyrich, Volker A Marti-Renom, Marc A Przybylski, Dariusz Madhusudhan, Mallur S Eswar, Narayanan Grana, Osvaldo Pazos, Florencio Valencia, Alfonso Sali, Andrej Rost, Burkhard 1-P50-GM62413-01/GM/NIGMS NIH HHS/United States 5-P20-LM7276/LM/NLM NIH HHS/United States P50 GM62529/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States R01-GM63029-01/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, Non-P.H.S. Research Support, U.S. Gov’t, P.H.S. England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3311-5.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Gordon, M. B.</style></author><author><style face="normal" font="default" size="100%">Perazzo, R.</style></author><author><style face="normal" font="default" size="100%">Risau-Gusman, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A model for the emergence of adaptive subsystems</style></title><secondary-title><style face="normal" font="default" size="100%">Bull Math Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Algorithms Alleles Animals Evolution Genotype Humans *Learning *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical Neural Networks (Computer) Phenotype Synapses/genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12597115</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">65</style></volume><pages><style face="normal" font="default" size="100%">27-56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We investigate the interaction of learning and evolution in a changing environment. A stable learning capability is regarded as an emergent adaptive system evolved by natural selection of genetic variants. We consider the evolution of an asexual population. Each genotype can have ’fixed’ and ’flexible’ alleles. The former express themselves as synaptic connections that remain unchanged during ontogeny and the latter as synapses that can be adjusted through a learning algorithm. Evolution is modelled using genetic algorithms and the changing environment is represented by two optimal synaptic patterns that alternate a fixed number of times during the ’life’ of the individuals. The amplitude of the change is related to the Hamming distance between the two optimal patterns and the rate of change to the frequency with which both exchange roles. This model is an extension of that of Hinton and Nowlan in which the fitness is given by a probabilistic measure of the Hamming distance to the optimum. We find that two types of evolutionary pathways are possible depending upon how difficult (costly) it is to cope with the changes of the environment. In one case the population loses the learning ability, and the individuals inherit fixed synapses that are optimal in only one of the environmental states. In the other case a flexible subsystem emerges that allows the individuals to adapt to the changes of the environment. The model helps us to understand how an adaptive subsystem can emerge as the result of the tradeoff between the exploitation of a congenital structure and the exploration of the adaptive capabilities practised by learning.</style></abstract><notes><style face="normal" font="default" size="100%">Dopazo, H Gordon, M B Perazzo, R Risau-Gusman, S Research Support, Non-U.S. Gov’t United States Bulletin of mathematical biology Bull Math Biol. 2003 Jan;65(1):27-56.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tracey, L.</style></author><author><style face="normal" font="default" size="100%">Villuendas, R.</style></author><author><style face="normal" font="default" size="100%">Ortiz, P.</style></author><author><style face="normal" font="default" size="100%">Dopazo, A.</style></author><author><style face="normal" font="default" size="100%">Spiteri, I.</style></author><author><style face="normal" font="default" size="100%">Lombardia, L.</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Peralto, J. L.</style></author><author><style face="normal" font="default" size="100%">Fernandez-Herrera, J.</style></author><author><style face="normal" font="default" size="100%">Hernandez, A.</style></author><author><style face="normal" font="default" size="100%">Fraga, J.</style></author><author><style face="normal" font="default" size="100%">Dominguez, O.</style></author><author><style face="normal" font="default" size="100%">Herrero, J.</style></author><author><style face="normal" font="default" size="100%">Alonso, M. A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Piris, M. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Pathol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antineoplastic Agents/*pharmacology/therapeutic use Carrier Proteins/biosynthesis/genetics DNA-Binding Proteins/biosynthesis/genetics Drug Resistance</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Oligonucleotide Array Sequence Analysis RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Cultured</style></keyword><keyword><style  face="normal" font="default" size="100%">Cutaneous/diagnosis/drug therapy/*genetics/metabolism *Membrane Glycoproteins Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Interleukin-1 Reproducibility of Results STAT1 Transcription Factor STAT3 Transcription Factor Trans-Activators/biosynthesis/genetics Tumor Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Gene Expression Profiling *Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm/biosynthesis *Receptors</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic Humans Interferon-alpha/*pharmacology/therapeutic use Kinetics Lymphoma</style></keyword><keyword><style  face="normal" font="default" size="100%">T-Cell</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12414529</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">161</style></volume><pages><style face="normal" font="default" size="100%">1825-37</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Interferon-alpha therapy has been shown to be active in the treatment of mycosis fungoides although the individual response to this therapy is unpredictable and dependent on essentially unknown factors. In an effort to better understand the molecular mechanisms of interferon-alpha resistance we have developed an interferon-alpha resistant variant from a sensitive cutaneous T-cell lymphoma cell line. We have performed expression analysis to detect genes differentially expressed between both variants using a cDNA microarray including 6386 cancer-implicated genes. The experiments showed that resistance to interferon-alpha is consistently associated with changes in the expression of a set of 39 genes, involved in signal transduction, apoptosis, transcription regulation, and cell growth. Additional studies performed confirm that STAT1 and STAT3 expression and interferon-alpha induction and activation are not altered between both variants. The gene MAL, highly overexpressed by resistant cells, was also found to be expressed by tumoral cells in a series of cutaneous T-cell lymphoma patients treated with interferon-alpha and/or photochemotherapy. MAL expression was associated with longer time to complete remission. Time-course experiments of the sensitive and resistant cells showed a differential expression of a subset of genes involved in interferon-response (1 to 4 hours), cell growth and apoptosis (24 to 48 hours.), and signal transduction.</style></abstract><notes><style face="normal" font="default" size="100%">Tracey, Lorraine Villuendas, Raquel Ortiz, Pablo Dopazo, Ana Spiteri, Inmaculada Lombardia, Luis Rodriguez-Peralto, Jose L Fernandez-Herrera, Jesus Hernandez, Almudena Fraga, Javier Dominguez, Orlando Herrero, Javier Alonso, Miguel A Dopazo, Joaquin Piris, Miguel A Research Support, Non-U.S. Gov’t United States The American journal of pathology Am J Pathol. 2002 Nov;161(5):1825-37.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reliability of assessment of protein structure prediction methods</style></title><secondary-title><style face="normal" font="default" size="100%">Structure</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Computer Simulation Humans *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular *Protein Conformation Proteins/*chemistry Reproducibility of Results</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12005441</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">435-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The reliability of ranking of protein structure modeling methods is assessed. The assessment is based on the parametric Student’s t test and the nonparametric Wilcox signed rank test of statistical significance of the difference between paired samples. The approach is applied to the ranking of the comparative modeling methods tested at the fourth meeting on Critical Assessment of Techniques for Protein Structure Prediction (CASP). It is shown that the 14 CASP4 test sequences may not be sufficient to reliably distinguish between the top eight methods, given the model quality differences and their standard deviations. We suggest that CASP needs to be supplemented by an assessment of protein structure prediction methods that is automated, continuous in time, based on several criteria applied to a large number of models, and with quantitative statistical reliability assigned to each characterization.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Marti-Renom, Marc A Madhusudhan, M S Fiser, Andras Rost, Burkhard Sali, Andrej GM 54762/GM/NIGMS NIH HHS/United States GM62413/GM/NIGMS NIH HHS/United States Comparative Study Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. United States Structure (London, England : 1993) Structure. 2002 Mar;10(3):435-40.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Iverson, G. M.</style></author><author><style face="normal" font="default" size="100%">Reddel, S.</style></author><author><style face="normal" font="default" size="100%">Victoria, E. J.</style></author><author><style face="normal" font="default" size="100%">Cockerill, K. A.</style></author><author><style face="normal" font="default" size="100%">Wang, Y. X.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Marquis, D. M.</style></author><author><style face="normal" font="default" size="100%">Krilis, S. A.</style></author><author><style face="normal" font="default" size="100%">Linnik, M. D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of single point mutations in domain I of beta 2-glycoprotein I to determine fine antigenic specificity of antiphospholipid autoantibodies</style></title><secondary-title><style face="normal" font="default" size="100%">J Immunol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution/genetics Antibodies</style></keyword><keyword><style  face="normal" font="default" size="100%">Antibody/genetics Binding</style></keyword><keyword><style  face="normal" font="default" size="100%">Antiphospholipid/blood/*metabolism Antibodies</style></keyword><keyword><style  face="normal" font="default" size="100%">Competitive/genetics/immunology Enzyme-Linked Immunosorbent Assay/methods Epitopes/analysis/*immunology/metabolism Glycine/genetics Glycoproteins/biosynthesis/*genetics/*immunology/isolation &amp; purification/metabolism Humans Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Peptide Fragments/genetics/immunology/isolation &amp; purification/metabolism *Point Mutation Protein Structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Monoclonal/blood/metabolism Antiphospholipid Syndrome/immunology Arginine/genetics *Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Tertiary/genetics Recombinant Proteins/biosynthesis/immunology/isolation &amp; purification/metabolism Static Electricity beta 2-Glycoprotein I</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12471146</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">169</style></volume><pages><style face="normal" font="default" size="100%">7097-103</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Autoantibodies against beta(2)-glycoprotein I (beta(2)GPI) appear to be a critical feature of the antiphospholipid syndrome (APS). As determined using domain deletion mutants, human autoantibodies bind to the first of five domains present in beta(2)GPI. In this study the fine detail of the domain I epitope has been examined using 10 selected mutants of whole beta(2)GPI containing single point mutations in the first domain. The binding to beta(2)GPI was significantly affected by a number of single point mutations in domain I, particularly by mutations in the region of aa 40-43. Molecular modeling predicted these mutations to affect the surface shape and electrostatic charge of a facet of domain I. Mutation K19E also had an effect, albeit one less severe and involving fewer patients. Similar results were obtained in two different laboratories using affinity-purified anti-beta(2)GPI in a competitive inhibition ELISA and with whole serum in a direct binding ELISA. This study confirms that anti-beta(2)GPI autoantibodies bind to domain I, and that the charged surface patch defined by residues 40-43 contributes to a dominant target epitope.</style></abstract><notes><style face="normal" font="default" size="100%">Iverson, G Michael Reddel, Stephen Victoria, Edward J Cockerill, Keith A Wang, Ying-Xia Marti-Renom, Marc A Sali, Andrej Marquis, David M Krilis, Steven A Linnik, Matthew D GM54762/GM/NIGMS NIH HHS/United States Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. United States Journal of immunology (Baltimore, Md. : 1950) J Immunol. 2002 Dec 15;169(12):7097-103.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Eyrich, V. A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Przybylski, D.</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Pazos, F.</style></author><author><style face="normal" font="default" size="100%">Valencia, A.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EVA: continuous automatic evaluation of protein structure prediction servers</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automation Internet *Protein Conformation Proteins/*analysis *Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=11751240</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">1242-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. AVAILABILITY: http://cubic.bioc.columbia.edu/eva. CONTACT: eva@cubic.bioc.columbia.edu</style></abstract><notes><style face="normal" font="default" size="100%">Eyrich, V A Marti-Renom, M A Przybylski, D Madhusudhan, M S Fiser, A Pazos, F Valencia, A Sali, A Rost, B England Bioinformatics (Oxford, England) Bioinformatics. 2001 Dec;17(12):1242-3.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Gordon, M. B.</style></author><author><style face="normal" font="default" size="100%">Perazzo, R.</style></author><author><style face="normal" font="default" size="100%">Risau-Gusman, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A model for the interaction of learning and evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Bull Math Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms Alleles Animals *Evolution Genotype Humans *Learning *Neural Networks (Computer) Numerical Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer-Assisted Phenotype Synapses/genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=11146879</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">63</style></volume><pages><style face="normal" font="default" size="100%">117-34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a simple model in order to discuss the interaction of the genetic and behavioral systems throughout evolution. This considers a set of adaptive perceptrons in which some of their synapses can be updated through a learning process. This framework provides an extension of the well-known Hinton and Nowlan model by blending together some learning capability and other (rigid) genetic effects that contribute to the fitness. We find a halting effect in the evolutionary dynamics, in which the transcription of environmental data into genetic information is hindered by learning, instead of stimulated as is usually understood by the so-called Baldwin effect. The present results are discussed and compared with those reported in the literature. An interpretation is provided of the halting effect.</style></abstract><notes><style face="normal" font="default" size="100%">Dopazo, H Gordon, M B Perazzo, R Risau-Gusman, S Comparative Study Research Support, Non-U.S. Gov’t United States Bulletin of mathematical biology Bull Math Biol. 2001 Jan;63(1):117-34.</style></notes></record></records></xml>