Produção Nacional
Revisado por pares
COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms
2021; Springer Nature; Volume: 17; Issue: 10 Linguagem: Inglês
10.15252/msb.202110387
ISSN1744-4292
AutoresMarek Ostaszewski, Anna Niarakis, Alexander Mazein, Inna Kuperstein, Robert D. Phair, Aurelio Orta‐Resendiz, Vidisha Singh, Sara Sadat Aghamiri, Márcio Luís Acencio, Enrico Glaab, Andreas Ruepp, Gisela Fobo, Corinna Montrone, Barbara Brauner, Goar Frishman, Luis Cristóbal Monraz Gómez, Julia Somers, Matti Hoch, Shailendra K. Gupta, Julia Scheel, Hanna Borlinghaus, Tobias Czauderna, Falk Schreiber, Arnau Montagud, Miguel Ponce-de-León, Akira Funahashi, Yusuke Hiki, Noriko Hiroi, Takahiro Yamada, Andreas Dräger, Alina Renz, Muhammad Naveez, Zsolt Böcskei, Francesco Messina, Daniela Börnigen, Liam Fergusson, Marta Zaffira Conti, Marius Rameil, Vanessa Nakonecnij, Jakob Vanhoefer, Leonard Schmiester, Muying Wang, Emily E. Ackerman, Jason E. Shoemaker, Jeremy Zucker, Kristie Oxford, Jeremy Teuton, Ebru Kocakaya, Gökçe Yağmur Summak, Kristina Hanspers, Martina Kutmon, Susan L. Coort, Lars Eijssen, Friederike Ehrhart, Rex Devasahayam Arokia Balaya, Denise Slenter, Marvin Martens, Nhung Pham, Robin Haw, Bijay Jassal, Lisa Matthews, M Orlic-Milacic, Andrea Senff‐Ribeiro, Karen Rothfels, Veronica Shamovsky, Ralf Stephan, Cristoffer Sevilla, Thawfeek Varusai, Jean‐Marie Ravel, Rupsha Fraser, Vera Ortseifen, Silvia Marchesi, Piotr Gawron, Ewa Smula, Laurent Heirendt, Venkata Satagopam, Guanming Wu, Anders Riutta, Martin Golebiewski, Stuart Owen, Carole Goble, Xiaoming Hu, Rupert W. Overall, Dieter Maier, Angela Bauch, Benjamin M. Gyori, John A. Bachman, Carlos Vega, Valentin Grouès, Miguél Vázquez, Pablo Porras, Luana Licata, Marta Iannuccelli, Francesca Sacco, Anastasia Nesterova, Anton Yuryev, Anita de Waard, Dénes Türei, Augustin Luna, Özgün Babur, Sylvain Soliman, Alberto Valdeolivas, Marina Esteban‐Medina, María Peña-Chilet, Kinza Rian, Tomáš Helikar, Bhanwar Lal Puniya, Dezső Módos, Agatha Treveil, Márton Ölbei, Bertrand De Meulder, Stéphane Ballereau, Aurélien Dugourd, Aurélien Naldi, Vincent Noël, Laurence Calzone, Chris Sander, Emek Demir, Tamás Korcsmáros, Tom C. Freeman, Franck Augé, J. Beckmann, Jan Hasenauer, Olaf Wolkenhauer, Egon Willighagen, Alexander R. Pico, Chris T. Evelo, Marc Gillespie, Lincoln Stein, Henning Hermjakob, Peter D’Eustachio, Julio Sáez-Rodríguez, Joaquı́n Dopazo, Alfonso Valencia, Hiroaki Kitano, Emmanuel Barillot, Charles Auffray, Rudi Balling, Reinhard Schneider,
Tópico(s)Microbial Metabolic Engineering and Bioproduction
ResumoWe 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.
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