04625nas a2201141 4500008004100000022001400041245011000055210006900165260000900234300001200243490000700255520126600262653002401528653001301552653002301565653001101588653001501599653002001614100001901634700002301653700002201676700002101698700002001719700002301739700002101762700002601783700001901809700002001828700001901848700002201867700002301889700002401912700001701936700002101953700001701974700001601991700002402007700002502031700002502056700002302081700002302104700002702127700002402154700001602178700002102194700002602215700002502241700002102266700002102287700001902308700003202327700002102359700002202380700002002402700001902422700002602441700001802467700001802485700002302503700002102526700001902547700001902566700002202585700001802607700001902625700001802644700002302662700001802685700002002703700001902723700003302742700002602775700002702801700002502828700002302853700001802876700002302894700001702917700002402934700001802958700002202976700002502998700002003023700002303043700002003066700002603086700002003112700001903132700002203151700002203173700002003195700002303215700002103238700001803259700002403277710003503301856014703336 2024 eng d a1664-322400aDrug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.0 aDrugtarget identification in COVID19 disease mechanisms using co c2023 a12828590 v143 a
INTRODUCTION: 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.
METHODS: 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.
RESULTS: 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.
DISCUSSION: 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.
10aComputer Simulation10aCOVID-1910adrug repositioning10aHumans10aSARS-CoV-210aSystems biology1 aNiarakis, Anna1 aOstaszewski, Marek1 aMazein, Alexander1 aKuperstein, Inna1 aKutmon, Martina1 aGillespie, Marc, E1 aFunahashi, Akira1 aAcencio, Marcio, Luis1 aHemedan, Ahmed1 aAichem, Michael1 aKlein, Karsten1 aCzauderna, Tobias1 aBurtscher, Felicia1 aYamada, Takahiro, G1 aHiki, Yusuke1 aHiroi, Noriko, F1 aHu, Finterly1 aPham, Nhung1 aEhrhart, Friederike1 aWillighagen, Egon, L1 aValdeolivas, Alberto1 aDugourd, Aurélien1 aMessina, Francesco1 aEsteban-Medina, Marina1 aPeña-Chilet, Maria1 aRian, Kinza1 aSoliman, Sylvain1 aAghamiri, Sara, Sadat1 aPuniya, Bhanwar, Lal1 aNaldi, Aurélien1 aHelikar, Tomáš1 aSingh, Vidisha1 aFernández, Marco, Fariñas1 aBermudez, Viviam1 aTsirvouli, Eirini1 aMontagud, Arnau1 aNoël, Vincent1 aPonce-de-Leon, Miguel1 aMaier, Dieter1 aBauch, Angela1 aGyori, Benjamin, M1 aBachman, John, A1 aLuna, Augustin1 aPiñero, Janet1 aFurlong, Laura, I1 aBalaur, Irina1 aRougny, Adrien1 aJarosz, Yohan1 aOverall, Rupert, W1 aPhair, Robert1 aPerfetto, Livia1 aMatthews, Lisa1 aRex, Devasahayam, Arokia Bal1 aOrlic-Milacic, Marija1 aGomez, Luis, Cristobal1 aDe Meulder, Bertrand1 aRavel, Jean, Marie1 aJassal, Bijay1 aSatagopam, Venkata1 aWu, Guanming1 aGolebiewski, Martin1 aGawron, Piotr1 aCalzone, Laurence1 aBeckmann, Jacques, S1 aEvelo, Chris, T1 aD'Eustachio, Peter1 aSchreiber, Falk1 aSaez-Rodriguez, Julio1 aDopazo, Joaquin1 aKuiper, Martin1 aValencia, Alfonso1 aWolkenhauer, Olaf1 aKitano, Hiroaki1 aBarillot, Emmanuel1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard1 aCOVID-19 Disease Map Community uhttps://www.clinbioinfosspa.es/content/drug-target-identification-covid-19-disease-mechanisms-using-computational-systems-biology-approaches-007193nas a2202077 4500008004100000022001400041245010000055210006900155260001200224300001100236490000700247520130900254653002101563653002601584653002201610653001301632653001401645653001601659653002301675653003101698653003201729653001101761653002301772653002201795653002101817653001601838653003601854653001801890653003201908653001501940653002401955653001301979653002601992653001902018100002302037700001902060700002202079700002102101700001802122700002702140700001902167700002602186700002602212700001802238700001902256700001702275700002202292700002102314700001902335700002902354700001802383700001602401700002902417700001802446700002302464700002202487700002002509700002002529700002702549700002102576700001702597700001802614700002402632700002102656700001602677700002102693700001902714700002302733700002302756700002002779700001702799700001902816700002402835700002102859700002402880700001702904700002302921700002402944700001902968700002002987700001903007700001903026700002903045700002303074700002003097700001703117700001803134700002403152700003303176700002003209700002003229700001603249700001503265700001803280700001903298700002603317700002703343700002003370700002403390700001803414700002403432700002203456700002203478700001903500700002003519700002103539700001803560700001503578700002203593700002303615700001703638700001903655700002403674700001703698700001803715700001703733700002303750700001803773700001803791700002303809700002103832700001703853700002203870700002003892700001803912700001803930700002303948700002103971700002503992700001804017700002004035700001704055700001904072700001704091700002104108700002504129700002704154700002404181700001604205700002104221700002504242700001704267700002004284700001804304700002504322700002404347700002304371700002104394700001904415700002204434700001804456700001604474700002204490700002004512700001804532700002504550700001904575700002204594700002404616700002304640700002004663700002304683700002204706700002304728700002304751700002604774700002004800700002204820700002004842700002304862700002104885700001804906700002404924710003504948856013204983 2021 eng d a1744-429200aCOVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.0 aCOVID19 Disease Map a computational knowledge repository of viru c2021 10 ae103870 v173 aWe 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.
10aAntiviral Agents10aComputational Biology10aComputer Graphics10aCOVID-1910aCytokines10aData Mining10aDatabases, Factual10aGene Expression Regulation10aHost Microbial Interactions10aHumans10aImmunity, Cellular10aImmunity, Humoral10aImmunity, Innate10aLymphocytes10aMetabolic Networks and Pathways10aMyeloid Cells10aProtein Interaction Mapping10aSARS-CoV-210aSignal Transduction10aSoftware10aTranscription Factors10aViral Proteins1 aOstaszewski, Marek1 aNiarakis, Anna1 aMazein, Alexander1 aKuperstein, Inna1 aPhair, Robert1 aOrta-Resendiz, Aurelio1 aSingh, Vidisha1 aAghamiri, Sara, Sadat1 aAcencio, Marcio, Luis1 aGlaab, Enrico1 aRuepp, Andreas1 aFobo, Gisela1 aMontrone, Corinna1 aBrauner, Barbara1 aFrishman, Goar1 aGómez, Luis, Cristóbal1 aSomers, Julia1 aHoch, Matti1 aGupta, Shailendra, Kumar1 aScheel, Julia1 aBorlinghaus, Hanna1 aCzauderna, Tobias1 aSchreiber, Falk1 aMontagud, Arnau1 ade Leon, Miguel, Ponce1 aFunahashi, Akira1 aHiki, Yusuke1 aHiroi, Noriko1 aYamada, Takahiro, G1 aDräger, Andreas1 aRenz, Alina1 aNaveez, Muhammad1 aBocskei, Zsolt1 aMessina, Francesco1 aBörnigen, Daniela1 aFergusson, Liam1 aConti, Marta1 aRameil, Marius1 aNakonecnij, Vanessa1 aVanhoefer, Jakob1 aSchmiester, Leonard1 aWang, Muying1 aAckerman, Emily, E1 aShoemaker, Jason, E1 aZucker, Jeremy1 aOxford, Kristie1 aTeuton, Jeremy1 aKocakaya, Ebru1 aSummak, Gökçe, Yağmur1 aHanspers, Kristina1 aKutmon, Martina1 aCoort, Susan1 aEijssen, Lars1 aEhrhart, Friederike1 aRex, Devasahayam, Arokia Bal1 aSlenter, Denise1 aMartens, Marvin1 aPham, Nhung1 aHaw, Robin1 aJassal, Bijay1 aMatthews, Lisa1 aOrlic-Milacic, Marija1 aRibeiro, Andrea, Senff1 aRothfels, Karen1 aShamovsky, Veronica1 aStephan, Ralf1 aSevilla, Cristoffer1 aVarusai, Thawfeek1 aRavel, Jean-Marie1 aFraser, Rupsha1 aOrtseifen, Vera1 aMarchesi, Silvia1 aGawron, Piotr1 aSmula, Ewa1 aHeirendt, Laurent1 aSatagopam, Venkata1 aWu, Guanming1 aRiutta, Anders1 aGolebiewski, Martin1 aOwen, Stuart1 aGoble, Carole1 aHu, Xiaoming1 aOverall, Rupert, W1 aMaier, Dieter1 aBauch, Angela1 aGyori, Benjamin, M1 aBachman, John, A1 aVega, Carlos1 aGrouès, Valentin1 aVazquez, Miguel1 aPorras, Pablo1 aLicata, Luana1 aIannuccelli, Marta1 aSacco, Francesca1 aNesterova, Anastasia1 aYuryev, Anton1 ade Waard, Anita1 aTurei, Denes1 aLuna, Augustin1 aBabur, Ozgun1 aSoliman, Sylvain1 aValdeolivas, Alberto1 aEsteban-Medina, Marina1 aPeña-Chilet, Maria1 aRian, Kinza1 aHelikar, Tomáš1 aPuniya, Bhanwar, Lal1 aModos, Dezso1 aTreveil, Agatha1 aOlbei, Marton1 aDe Meulder, Bertrand1 aBallereau, Stephane1 aDugourd, Aurélien1 aNaldi, Aurélien1 aNoël, Vincent1 aCalzone, Laurence1 aSander, Chris1 aDemir, Emek1 aKorcsmaros, Tamas1 aFreeman, Tom, C1 aAugé, Franck1 aBeckmann, Jacques, S1 aHasenauer, Jan1 aWolkenhauer, Olaf1 aWilighagen, Egon, L1 aPico, Alexander, R1 aEvelo, Chris, T1 aGillespie, Marc, E1 aStein, Lincoln, D1 aHermjakob, Henning1 aD'Eustachio, Peter1 aSaez-Rodriguez, Julio1 aDopazo, Joaquin1 aValencia, Alfonso1 aKitano, Hiroaki1 aBarillot, Emmanuel1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard1 aCOVID-19 Disease Map Community uhttps://www.clinbioinfosspa.es/content/covid19-disease-map-computational-knowledge-repository-virus-host-interaction-mechanisms01798nas a2200577 4500008004100000022001400041245011100055210006900166260001500235300000800250490000600258653002000264653002600284653002700310653001300337653002300350653003200373653003100405653001100436653003000447653002300477653001400500653002100514653001500535100002300550700002200573700002300595700002100618700001900639700002300658700002300681700002500704700002000729700001900749700002000768700002100788700001600809700002200825700002200847700002300869700002000892700002700912700002300939700002200962700002100984700002001005700002101025700001801046700002401064856013201088 2020 eng d a2052-446300aCOVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms.0 aCOVID19 Disease Map building a computational repository of SARSC c2020 05 05 a1360 v710aBetacoronavirus10aComputational Biology10aCoronavirus Infections10aCOVID-1910aDatabases, Factual10aHost Microbial Interactions10aHost-Pathogen Interactions10aHumans10aInternational Cooperation10aModels, Biological10aPandemics10aPneumonia, Viral10aSARS-CoV-21 aOstaszewski, Marek1 aMazein, Alexander1 aGillespie, Marc, E1 aKuperstein, Inna1 aNiarakis, Anna1 aHermjakob, Henning1 aPico, Alexander, R1 aWillighagen, Egon, L1 aEvelo, Chris, T1 aHasenauer, Jan1 aSchreiber, Falk1 aDräger, Andreas1 aDemir, Emek1 aWolkenhauer, Olaf1 aFurlong, Laura, I1 aBarillot, Emmanuel1 aDopazo, Joaquin1 aOrta-Resendiz, Aurelio1 aMessina, Francesco1 aValencia, Alfonso1 aFunahashi, Akira1 aKitano, Hiroaki1 aAuffray, Charles1 aBalling, Rudi1 aSchneider, Reinhard uhttps://www.clinbioinfosspa.es/content/covid-19-disease-map-building-computational-repository-sars-cov-2-virus-host-interaction03125nas a2200673 4500008004100000022001400041245010800055210006900163260000900232490000600241520108900247653002601336653003101362653004201393653001101435100001901446700002101465700002001486700001901506700003301525700002701558700003501585700002001620700002201640700001201662700001801674700002201692700001301714700002101727700002001748700002101768700001801789700001801807700002601825700001801851700001601869700002401885700001801909700002101927700001701948700002701965700001801992700002302010700001902033700002702052700001402079700002302093700001702116700001902133700001502152700002202167700002102189700002202210700001702232700003202249700001802281700002402299856012802323 2020 eng d a2046-140200aThe ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research.0 aELIXIR Human Copy Number Variations Community building bioinform c20200 v93 aCopy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" 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.
10aComputational Biology10aDNA Copy Number Variations10aHigh-Throughput Nucleotide Sequencing10aHumans1 aSalgado, David1 aArmean, Irina, M1 aBaudis, Michael1 aBeltran, Sergi1 aCapella-Gutíerrez, Salvador1 aCarvalho-Silva, Denise1 aDel Angel, Victoria, Dominguez1 aDopazo, Joaquin1 aFurlong, Laura, I1 aGao, Bo1 aGarcia, Leyla1 aGerloff, Dietlind1 aGut, Ivo1 aGyenesei, Attila1 aHabermann, Nina1 aHancock, John, M1 aHanauer, Marc1 aHovig, Eivind1 aJohansson, Lennart, F1 aKeane, Thomas1 aKorbel, Jan1 aLauer, Katharina, B1 aLaurie, Steve1 aLeskošek, Brane1 aLloyd, David1 aMarqués-Bonet, Tomás1 aMei, Hailiang1 aMonostory, Katalin1 aPiñero, Janet1 aPoterlowicz, Krzysztof1 aRath, Ana1 aSamarakoon, Pubudu1 aSanz, Ferran1 aSaunders, Gary1 aSie, Daoud1 aSwertz, Morris, A1 aTsukanov, Kirill1 aValencia, Alfonso1 aVidak, Marko1 aGonzález, Cristina, Yenyxe1 aYlstra, Bauke1 aBéroud, Christophe uhttps://www.clinbioinfosspa.es/content/elixir-human-copy-number-variations-community-building-bioinformatics-infrastructure02194nas a2200241 4500008004100000022001400041245006800055210006700123260001500190300001200205490000700217520142700224653001901651653002601670653001101696653002301707100002701730700002001757700002201777700002201799700002501821856010601846 2019 eng d a1477-405400aPrecision medicine needs pioneering clinical bioinformaticians.0 aPrecision medicine needs pioneering clinical bioinformaticians c2019 05 21 a752-7660 v203 aSuccess in precision medicine depends on accessing high-quality genetic and molecular data from large, well-annotated patient cohorts that couple biological samples to comprehensive clinical data, which in conjunction can lead to effective therapies. From such a scenario emerges the need for a new professional profile, an expert bioinformatician with training in clinical areas who can make sense of multi-omics data to improve therapeutic interventions in patients, and the design of optimized basket trials. In this review, we first describe the main policies and international initiatives that focus on precision medicine. Secondly, we review the currently ongoing clinical trials in precision medicine, introducing the concept of 'precision bioinformatics', and we describe current pioneering bioinformatics efforts aimed at implementing tools and computational infrastructures for precision medicine in health institutions around the world. Thirdly, we discuss the challenges related to the clinical training of bioinformaticians, and the urgent need for computational specialists capable of assimilating medical terminologies and protocols to address real clinical questions. We also propose some skills required to carry out common tasks in clinical bioinformatics and some tips for emergent groups. Finally, we explore the future perspectives and the challenges faced by precision medicine bioinformatics.
10aCohort Studies10aComputational Biology10aHumans10aPrecision Medicine1 aGómez-López, Gonzalo1 aDopazo, Joaquin1 aCigudosa, Juan, C1 aValencia, Alfonso1 aAl-Shahrour, Fátima uhttps://www.clinbioinfosspa.es/content/precision-medicine-needs-pioneering-clinical-bioinformaticians03690nas a2200937 4500008004100000022001400041245007800055210006900133260001300202300001100215490000600226520100100232653002601233653003201259653002301291653003801314653001301352653002601365653002401391110002301415700002301438700001901461700001801480700002501498700001801523700001901541700002101560700001601581700001601597700002901613700001701642700001901659700002201678700002501700700003101725700002501756700001601781700001901797700001601816700002001832700002601852700002501878700001901903700001901922700001801941700001901959700001401978700001901992700002002011700002002031700001702051700002002068700002102088700002402109700002102133700002102154700002102175700002202196700001802218700002002236700002302256700002402279700002502303700002002328700002002348700002002368700002002388700002202408700002002430700002302450700001702473700001602490700002702506700001802533700001802551700001902569700002002588700001802608700002302626856010302649 2008 eng d a1477-405400aInteroperability with Moby 1.0--it's better than sharing your toothbrush!0 aInteroperability with Moby 10its better than sharing your toothb c2008 May a220-310 v93 aThe 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/.
10aComputational Biology10aDatabase Management Systems10aDatabases, Factual10aInformation Storage and Retrieval10aInternet10aProgramming Languages10aSystems Integration1 aBioMoby Consortium1 aWilkinson, Mark, D1 aSenger, Martin1 aKawas, Edward1 aBruskiewich, Richard1 aGouzy, Jerome1 aNoirot, Celine1 aBardou, Philippe1 aNg, Ambrose1 aHaase, Dirk1 aSaiz, Enrique, de Andres1 aWang, Dennis1 aGibbons, Frank1 aGordon, Paul, M K1 aSensen, Christoph, W1 aCarrasco, Jose, Manuel Rod1 aFernández, José, M1 aShen, Lixin1 aLinks, Matthew1 aNg, Michael1 aOpushneva, Nina1 aNeerincx, Pieter, B T1 aLeunissen, Jack, A M1 aErnst, Rebecca1 aTwigger, Simon1 aUsadel, Bjorn1 aGood, Benjamin1 aWong, Yan1 aStein, Lincoln1 aCrosby, William1 aKarlsson, Johan1 aRoyo, Romina1 aPárraga, Iván1 aRamírez, Sergio1 aGelpi, Josep, Lluis1 aTrelles, Oswaldo1 aPisano, David, G1 aJimenez, Natalia1 aKerhornou, Arnaud1 aRosset, Roman1 aZamacola, Leire1 aTárraga, Joaquín1 aHuerta-Cepas, Jaime1 aCarazo, Jose, María1 aDopazo, Joaquin1 aGuigó, Roderic1 aNavarro, Arcadi1 aOrozco, Modesto1 aValencia, Alfonso1 aClaros, Gonzalo1 aPérez, Antonio, J1 aAldana, Jose1 aRojano, Mar1 aCruz, Raul, Fernandez-1 aNavas, Ismael1 aSchiltz, Gary1 aFarmer, Andrew1 aGessler, Damian1 aSchoof, Heiko1 aGroscurth, Andreas uhttps://www.clinbioinfosspa.es/content/interoperability-moby-10-its-better-sharing-your-toothbrush