%0 Journal Article %J Front Immunol %D 2024 %T Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. %A Niarakis, Anna %A Ostaszewski, Marek %A Mazein, Alexander %A Kuperstein, Inna %A Kutmon, Martina %A Gillespie, Marc E %A Funahashi, Akira %A Acencio, Marcio Luis %A Hemedan, Ahmed %A Aichem, Michael %A Klein, Karsten %A Czauderna, Tobias %A Burtscher, Felicia %A Yamada, Takahiro G %A Hiki, Yusuke %A Hiroi, Noriko F %A Hu, Finterly %A Pham, Nhung %A Ehrhart, Friederike %A Willighagen, Egon L %A Valdeolivas, Alberto %A Dugourd, Aurélien %A Messina, Francesco %A Esteban-Medina, Marina %A Peña-Chilet, Maria %A Rian, Kinza %A Soliman, Sylvain %A Aghamiri, Sara Sadat %A Puniya, Bhanwar Lal %A Naldi, Aurélien %A Helikar, Tomáš %A Singh, Vidisha %A Fernández, Marco Fariñas %A Bermudez, Viviam %A Tsirvouli, Eirini %A Montagud, Arnau %A Noël, Vincent %A Ponce-de-Leon, Miguel %A Maier, Dieter %A Bauch, Angela %A Gyori, Benjamin M %A Bachman, John A %A Luna, Augustin %A Piñero, Janet %A Furlong, Laura I %A Balaur, Irina %A Rougny, Adrien %A Jarosz, Yohan %A Overall, Rupert W %A Phair, Robert %A Perfetto, Livia %A Matthews, Lisa %A Rex, Devasahayam Arokia Balaya %A Orlic-Milacic, Marija %A Gomez, Luis Cristobal Monraz %A De Meulder, Bertrand %A Ravel, Jean Marie %A Jassal, Bijay %A Satagopam, Venkata %A Wu, Guanming %A Golebiewski, Martin %A Gawron, Piotr %A Calzone, Laurence %A Beckmann, Jacques S %A Evelo, Chris T %A D'Eustachio, Peter %A Schreiber, Falk %A Saez-Rodriguez, Julio %A Dopazo, Joaquin %A Kuiper, Martin %A Valencia, Alfonso %A Wolkenhauer, Olaf %A Kitano, Hiroaki %A Barillot, Emmanuel %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Computer Simulation %K COVID-19 %K drug repositioning %K Humans %K SARS-CoV-2 %K Systems biology %X

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.

%B Front Immunol %V 14 %P 1282859 %8 2023 %G eng %R 10.3389/fimmu.2023.1282859 %0 Journal Article %J Mol Syst Biol %D 2021 %T COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. %A Ostaszewski, Marek %A Niarakis, Anna %A Mazein, Alexander %A Kuperstein, Inna %A Phair, Robert %A Orta-Resendiz, Aurelio %A Singh, Vidisha %A Aghamiri, Sara Sadat %A Acencio, Marcio Luis %A Glaab, Enrico %A Ruepp, Andreas %A Fobo, Gisela %A Montrone, Corinna %A Brauner, Barbara %A Frishman, Goar %A Monraz Gómez, Luis Cristóbal %A Somers, Julia %A Hoch, Matti %A Kumar Gupta, Shailendra %A Scheel, Julia %A Borlinghaus, Hanna %A Czauderna, Tobias %A Schreiber, Falk %A Montagud, Arnau %A Ponce de Leon, Miguel %A Funahashi, Akira %A Hiki, Yusuke %A Hiroi, Noriko %A Yamada, Takahiro G %A Dräger, Andreas %A Renz, Alina %A Naveez, Muhammad %A Bocskei, Zsolt %A Messina, Francesco %A Börnigen, Daniela %A Fergusson, Liam %A Conti, Marta %A Rameil, Marius %A Nakonecnij, Vanessa %A Vanhoefer, Jakob %A Schmiester, Leonard %A Wang, Muying %A Ackerman, Emily E %A Shoemaker, Jason E %A Zucker, Jeremy %A Oxford, Kristie %A Teuton, Jeremy %A Kocakaya, Ebru %A Summak, Gökçe Yağmur %A Hanspers, Kristina %A Kutmon, Martina %A Coort, Susan %A Eijssen, Lars %A Ehrhart, Friederike %A Rex, Devasahayam Arokia Balaya %A Slenter, Denise %A Martens, Marvin %A Pham, Nhung %A Haw, Robin %A Jassal, Bijay %A Matthews, Lisa %A Orlic-Milacic, Marija %A Senff Ribeiro, Andrea %A Rothfels, Karen %A Shamovsky, Veronica %A Stephan, Ralf %A Sevilla, Cristoffer %A Varusai, Thawfeek %A Ravel, Jean-Marie %A Fraser, Rupsha %A Ortseifen, Vera %A Marchesi, Silvia %A Gawron, Piotr %A Smula, Ewa %A Heirendt, Laurent %A Satagopam, Venkata %A Wu, Guanming %A Riutta, Anders %A Golebiewski, Martin %A Owen, Stuart %A Goble, Carole %A Hu, Xiaoming %A Overall, Rupert W %A Maier, Dieter %A Bauch, Angela %A Gyori, Benjamin M %A Bachman, John A %A Vega, Carlos %A Grouès, Valentin %A Vazquez, Miguel %A Porras, Pablo %A Licata, Luana %A Iannuccelli, Marta %A Sacco, Francesca %A Nesterova, Anastasia %A Yuryev, Anton %A de Waard, Anita %A Turei, Denes %A Luna, Augustin %A Babur, Ozgun %A Soliman, Sylvain %A Valdeolivas, Alberto %A Esteban-Medina, Marina %A Peña-Chilet, Maria %A Rian, Kinza %A Helikar, Tomáš %A Puniya, Bhanwar Lal %A Modos, Dezso %A Treveil, Agatha %A Olbei, Marton %A De Meulder, Bertrand %A Ballereau, Stephane %A Dugourd, Aurélien %A Naldi, Aurélien %A Noël, Vincent %A Calzone, Laurence %A Sander, Chris %A Demir, Emek %A Korcsmaros, Tamas %A Freeman, Tom C %A Augé, Franck %A Beckmann, Jacques S %A Hasenauer, Jan %A Wolkenhauer, Olaf %A Wilighagen, Egon L %A Pico, Alexander R %A Evelo, Chris T %A Gillespie, Marc E %A Stein, Lincoln D %A Hermjakob, Henning %A D'Eustachio, Peter %A Saez-Rodriguez, Julio %A Dopazo, Joaquin %A Valencia, Alfonso %A Kitano, Hiroaki %A Barillot, Emmanuel %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Antiviral Agents %K Computational Biology %K Computer Graphics %K COVID-19 %K Cytokines %K Data Mining %K Databases, Factual %K Gene Expression Regulation %K Host Microbial Interactions %K Humans %K Immunity, Cellular %K Immunity, Humoral %K Immunity, Innate %K Lymphocytes %K Metabolic Networks and Pathways %K Myeloid Cells %K Protein Interaction Mapping %K SARS-CoV-2 %K Signal Transduction %K Software %K Transcription Factors %K Viral Proteins %X

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.

%B Mol Syst Biol %V 17 %P e10387 %8 2021 10 %G eng %N 10 %1 https://www.ncbi.nlm.nih.gov/pubmed/34664389?dopt=Abstract %R 10.15252/msb.202110387 %0 Journal Article %J Sci Data %D 2020 %T COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. %A Ostaszewski, Marek %A Mazein, Alexander %A Gillespie, Marc E %A Kuperstein, Inna %A Niarakis, Anna %A Hermjakob, Henning %A Pico, Alexander R %A Willighagen, Egon L %A Evelo, Chris T %A Hasenauer, Jan %A Schreiber, Falk %A Dräger, Andreas %A Demir, Emek %A Wolkenhauer, Olaf %A Furlong, Laura I %A Barillot, Emmanuel %A Dopazo, Joaquin %A Orta-Resendiz, Aurelio %A Messina, Francesco %A Valencia, Alfonso %A Funahashi, Akira %A Kitano, Hiroaki %A Auffray, Charles %A Balling, Rudi %A Schneider, Reinhard %K Betacoronavirus %K Computational Biology %K Coronavirus Infections %K COVID-19 %K Databases, Factual %K Host Microbial Interactions %K Host-Pathogen Interactions %K Humans %K International Cooperation %K Models, Biological %K Pandemics %K Pneumonia, Viral %K SARS-CoV-2 %B Sci Data %V 7 %P 136 %8 2020 05 05 %G eng %N 1 %1 https://www.ncbi.nlm.nih.gov/pubmed/32371892?dopt=Abstract %R 10.1038/s41597-020-0477-8 %0 Journal Article %J F1000Res %D 2020 %T The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research. %A Salgado, David %A Armean, Irina M %A Baudis, Michael %A Beltran, Sergi %A Capella-Gutíerrez, Salvador %A Carvalho-Silva, Denise %A Dominguez Del Angel, Victoria %A Dopazo, Joaquin %A Furlong, Laura I %A Gao, Bo %A Garcia, Leyla %A Gerloff, Dietlind %A Gut, Ivo %A Gyenesei, Attila %A Habermann, Nina %A Hancock, John M %A Hanauer, Marc %A Hovig, Eivind %A Johansson, Lennart F %A Keane, Thomas %A Korbel, Jan %A Lauer, Katharina B %A Laurie, Steve %A Leskošek, Brane %A Lloyd, David %A Marqués-Bonet, Tomás %A Mei, Hailiang %A Monostory, Katalin %A Piñero, Janet %A Poterlowicz, Krzysztof %A Rath, Ana %A Samarakoon, Pubudu %A Sanz, Ferran %A Saunders, Gary %A Sie, Daoud %A Swertz, Morris A %A Tsukanov, Kirill %A Valencia, Alfonso %A Vidak, Marko %A Yenyxe González, Cristina %A Ylstra, Bauke %A Béroud, Christophe %K Computational Biology %K DNA Copy Number Variations %K High-Throughput Nucleotide Sequencing %K Humans %X

Copy 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.

%B F1000Res %V 9 %8 2020 %G eng %1 https://www.ncbi.nlm.nih.gov/pubmed/34367618?dopt=Abstract %& 1229 %R 10.12688/f1000research.24887.1 %0 Journal Article %J Brief Bioinform %D 2019 %T Precision medicine needs pioneering clinical bioinformaticians. %A Gómez-López, Gonzalo %A Dopazo, Joaquin %A Cigudosa, Juan C %A Valencia, Alfonso %A Al-Shahrour, Fátima %K Cohort Studies %K Computational Biology %K Humans %K Precision Medicine %X

Success 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.

%B Brief Bioinform %V 20 %P 752-766 %8 2019 05 21 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/29077790?dopt=Abstract %R 10.1093/bib/bbx144 %0 Journal Article %J Brief Bioinform %D 2008 %T Interoperability with Moby 1.0--it's better than sharing your toothbrush! %A Wilkinson, Mark D %A Senger, Martin %A Kawas, Edward %A Bruskiewich, Richard %A Gouzy, Jerome %A Noirot, Celine %A Bardou, Philippe %A Ng, Ambrose %A Haase, Dirk %A Saiz, Enrique de Andres %A Wang, Dennis %A Gibbons, Frank %A Gordon, Paul M K %A Sensen, Christoph W %A Carrasco, Jose Manuel Rodriguez %A Fernández, José M %A Shen, Lixin %A Links, Matthew %A Ng, Michael %A Opushneva, Nina %A Neerincx, Pieter B T %A Leunissen, Jack A M %A Ernst, Rebecca %A Twigger, Simon %A Usadel, Bjorn %A Good, Benjamin %A Wong, Yan %A Stein, Lincoln %A Crosby, William %A Karlsson, Johan %A Royo, Romina %A Párraga, Iván %A Ramírez, Sergio %A Gelpi, Josep Lluis %A Trelles, Oswaldo %A Pisano, David G %A Jimenez, Natalia %A Kerhornou, Arnaud %A Rosset, Roman %A Zamacola, Leire %A Tárraga, Joaquín %A Huerta-Cepas, Jaime %A Carazo, Jose María %A Dopazo, Joaquin %A Guigó, Roderic %A Navarro, Arcadi %A Orozco, Modesto %A Valencia, Alfonso %A Claros, M Gonzalo %A Pérez, Antonio J %A Aldana, Jose %A Rojano, M Mar %A Fernandez-Santa Cruz, Raul %A Navas, Ismael %A Schiltz, Gary %A Farmer, Andrew %A Gessler, Damian %A Schoof, Heiko %A Groscurth, Andreas %K Computational Biology %K Database Management Systems %K Databases, Factual %K Information Storage and Retrieval %K Internet %K Programming Languages %K Systems Integration %X

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/.

%B Brief Bioinform %V 9 %P 220-31 %8 2008 May %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/18238804?dopt=Abstract %R 10.1093/bib/bbn003