COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

TitleCOVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.
Publication TypeJournal Article
Year of Publication2021
AuthorsOstaszewski, M, Niarakis, A, Mazein, A, Kuperstein, I, Phair, R, Orta-Resendiz, A, Singh, V, Aghamiri, SSadat, Acencio, MLuis, Glaab, E, Ruepp, A, Fobo, G, Montrone, C, Brauner, B, Frishman, G, Gómez, LCristóbal, Somers, J, Hoch, M, Gupta, SKumar, Scheel, J, Borlinghaus, H, Czauderna, T, Schreiber, F, Montagud, A, de Leon, MPonce, Funahashi, A, Hiki, Y, Hiroi, N, Yamada, TG, Dräger, A, Renz, A, Naveez, M, Bocskei, Z, Messina, F, Börnigen, D, Fergusson, L, Conti, M, Rameil, M, Nakonecnij, V, Vanhoefer, J, Schmiester, L, Wang, M, Ackerman, EE, Shoemaker, JE, Zucker, J, Oxford, K, Teuton, J, Kocakaya, E, Summak, GYağmur, Hanspers, K, Kutmon, M, Coort, S, Eijssen, L, Ehrhart, F, Rex, DArokia Bal, Slenter, D, Martens, M, Pham, N, Haw, R, Jassal, B, Matthews, L, Orlic-Milacic, M, Ribeiro, ASenff, Rothfels, K, Shamovsky, V, Stephan, R, Sevilla, C, Varusai, T, Ravel, J-M, Fraser, R, Ortseifen, V, Marchesi, S, Gawron, P, Smula, E, Heirendt, L, Satagopam, V, Wu, G, Riutta, A, Golebiewski, M, Owen, S, Goble, C, Hu, X, Overall, RW, Maier, D, Bauch, A, Gyori, BM, Bachman, JA, Vega, C, Grouès, V, Vazquez, M, Porras, P, Licata, L, Iannuccelli, M, Sacco, F, Nesterova, A, Yuryev, A, de Waard, A, Turei, D, Luna, A, Babur, O, Soliman, S, Valdeolivas, A, Esteban-Medina, M, Peña-Chilet, M, Rian, K, Helikar, T, Puniya, BLal, Modos, D, Treveil, A, Olbei, M, De Meulder, B, Ballereau, S, Dugourd, A, Naldi, A, Noël, V, Calzone, L, Sander, C, Demir, E, Korcsmaros, T, Freeman, TC, Augé, F, Beckmann, JS, Hasenauer, J, Wolkenhauer, O, Wilighagen, EL, Pico, AR, Evelo, CT, Gillespie, ME, Stein, LD, Hermjakob, H, D'Eustachio, P, Saez-Rodriguez, J, Dopazo, J, Valencia, A, Kitano, H, Barillot, E, Auffray, C, Balling, R, Schneider, R
Corporate AuthorsCOVID-19 Disease Map Community
JournalMol Syst Biol
Date Published2021 10
KeywordsAntiviral Agents; Computational Biology; Computer Graphics; COVID-19; Cytokines; Data Mining; Databases, Factual; Gene Expression Regulation; Host Microbial Interactions; Humans; Immunity, Cellular; Immunity, Humoral; Immunity, Innate; Lymphocytes; Metabolic Networks and Pathways; Myeloid Cells; Protein Interaction Mapping; SARS-CoV-2; Signal Transduction; Software; Transcription Factors; Viral Proteins

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.

Alternate JournalMol Syst Biol
PubMed ID34664389
PubMed Central IDPMC8524328
Grant ListU41 HG003751 / HG / NHGRI NIH HHS / United States
H2020-ICT-825070 / / EC | H2020 | H2020 Priority Industrial Leadership | LEIT | H2020 LEIT Information and Communication Technologies (ICT) /
765274 / / H2020 Marie Skłodowska-Curie Actions /
10430012010015 / / The Netherlands Organisation for Health Research and Development (ZonMw) /
/ / Bundesministerium für Bildung und Forschung (BMBF) /
2020/0766 / / Association Nationale de la Recherche et de la Technologie (ANRT) /
8020708703 / / Deutsches Zentrum für Infektionsforschung (DZIF) /
COVID-19/2020-1/14715687/CovScreen / / Fonds National de la Recherche Luxembourg (FNR) /
H2020-ICT-951773 / / EC | H2020 | H2020 Priority Industrial Leadership | LEIT | H2020 LEIT Information and Communication Technologies (ICT) /
U41 HG003751 / HG / NHGRI NIH HHS / United States