Paper

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

Sander, Chris, Wu, Guanming, Schneider, Reinhard, Montrone, Corinna, Mazein, Alexander, Evelo, Chris T, Schmiester, Leonard, Jassal, Bijay, Kinza Rian, Valencia, Alfonso, Smula, Ewa, Oxford, Kristie, Martens, Marvin, Naveez, Muhammad, Stein, Lincoln D, Bertrand De Meulder, Noë, Vincent, Rex, D A B, Vazquez, Miguel, Barillot, Emmanuel, The Covid-19 Disease Map Community, Brauner, Barbara, Peter D’eustachio, Conti, Marta, Modos, Dezso, Teuton, Jeremy, Hasenauer, Jan, Börnigen, Daniela, Iannuccelli, Marta, Bhanwar Lal Puniya, Montagud, Arnau, Korcsmaros, Tamas, Pico, Alexander R, Rameil, Marius, Fergusson, Liam, Zucker, Jeremy, Satagopam, Venkata, Golebiewski, Martin, Funahashi, Akira, Luis Cristóbal Monraz Gómez, Matthews, Lisa, Varusai, Thawfeek, Saez-Rodriguez, Julio, Singh, Vidisha, Messina, Francesco, Coort, Susan, Fraser, Rupsha, Shoemaker, Jason, Dopazo, Joaquin, Sara Sadat Aghamiri, Phair, Robert, Kutmon, Martina, Marton Olbei, Schreiber, Falk, Ponce De Leon, Miguel, Hu, Xiaoming, Nakonecnij, Vanessa, De Waard, Anita, Dugourd, Aurélien, Andrea Senff Ribeiro, Helikar, Tomáš, Orta-Resendiz, Aurelio, Gökç

2021

Overview

Abstract 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. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses. Competing Interest Statement D. Maier and A. Bauch are employed at Biomax Informatics AG and will be affected by any effect of this publication on the commercial version of the AILANI software. J.A. Bachman and B. Gyori received consulting fees from Two Six Labs, LLC. T. Helikar has served as a shareholder and/or has consulted for Discovery Collective, Inc. R. Balling and R. Schneider are founders and shareholders of MEGENO S.A. and ITTM S.A. Remaining authors have declared no competing interests. Footnotes * ↵81 FAIRDOMHub: https://fairdomhub.org/projects/190 * This version introduces small revisions of the authors' affiliations and ORCIDs * http://doi.org/10.17881/covid19-disease-map * https://fairdomhub.org/projects/190 * 4 https://fairdomhub.org/documents/661 * 5 https://reactome.org/community/training * 6 https://www.wikipathways.org/index.php/Help:Editing_Pathways * 7 http://celldesigner.org * 8 https://newteditor.org * 9 https://github.com/sbgn/ySBGN * 12 https://www.ebi.ac.uk/intact/imex/main.xhtml?query=annot:“dataset:coronavirus” * 13 https://signor.uniroma2.it/covid/

• Publisher: Cold Spring Harbor Laboratory Press,Cold Spring Harbor Laboratory
• Subject: Computer applications / Coronaviruses / COVID-19 / Informatics / Molecular modelling / Severe acute respiratory syndrome coronavirus 2 / Systems Biology