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

Authors :
Ostaszewski, Marek
Niarakis, Anna
Mazein, Alexander
Kuperstein, Inna
Phair, Robert
Orta-Resendiz, Aurelio
Singh, Vidisha
Aghamiri, Sara Sadat
Acencio, Marcio Luis
Glaab, Enrico
Ruepp, Andreas
Fobo, Gisela
Montrone, Corinna
Brauner, Barbara
Frishman, Goar
Monraz G��mez, Luis Crist��bal
Somers, Julia
Hoch, Matti
Kumar Gupta, Shailendra
Scheel, Julia
Borlinghaus, Hanna
Czauderna, Tobias
Schreiber, Falk
Montagud, Arnau
Ponce De Leon, Miguel
Funahashi, Akira
Hiki, Yusuke
Hiroi, Noriko
Yamada, Takahiro G
Dr��ger, Andreas
Renz, Alina
Naveez, Muhammad
Bocskei, Zsolt
Messina, Francesco
B��rnigen, Daniela
Fergusson, Liam
Conti, Marta
Rameil, Marius
Nakonecnij, Vanessa
Vanhoefer, Jakob
Schmiester, Leonard
Wang, Muying
Ackerman, Emily E
Shoemaker, Jason E
Zucker, Jeremy
Oxford, Kristie
Teuton, Jeremy
Kocakaya, Ebru
Summak, G��k��e Ya��mur
Hanspers, Kristina
Kutmon, Martina
Coort, Susan
Eijssen, Lars
Ehrhart, Friederike
Rex, Devasahayam Arokia Balaya
Slenter, Denise
Martens, Marvin
Pham, Nhung
Haw, Robin
Jassal, Bijay
Matthews, Lisa
Orlic-Milacic, Marija
Senff Ribeiro, Andrea
Rothfels, Karen
Shamovsky, Veronica
Stephan, Ralf
Sevilla, Cristoffer
Varusai, Thawfeek
Ravel, Jean-Marie
Fraser, Rupsha
Ortseifen, Vera
Marchesi, Silvia
Gawron, Piotr
Smula, Ewa
Heirendt, Laurent
Satagopam, Venkata
Wu, Guanming
Riutta, Anders
Golebiewski, Martin
Owen, Stuart
Goble, Carole
Hu, Xiaoming
Overall, Rupert W
Maier, Dieter
Bauch, Angela
Gyori, Benjamin M
Bachman, John A
Vega, Carlos
Grou��s, Valentin
Vazquez, Miguel
Porras, Pablo
Licata, Luana
Iannuccelli, Marta
Sacco, Francesca
Nesterova, Anastasia
Yuryev, Anton
De Waard, Anita
Turei, Denes
Luna, Augustin
Babur, Ozgun
Soliman, Sylvain
Valdeolivas, Alberto
Esteban-Medina, Marina
Pe��a-Chilet, Maria
Rian, Kinza
Helikar, Tom����
Puniya, Bhanwar Lal
Modos, Dezso
Treveil, Agatha
Olbei, Marton
De Meulder, Bertrand
Ballereau, Stephane
Dugourd, Aur��lien
Naldi, Aur��lien
No��l, Vincent
Calzone, Laurence
Sander, Chris
Demir, Emek
Korcsmaros, Tamas
Freeman, Tom C
Aug��, Franck
Beckmann, Jacques S
Hasenauer, Jan
Wolkenhauer, Olaf
Wilighagen, Egon L
Pico, Alexander R
Evelo, Chris T
Gillespie, Marc E
Stein, Lincoln D
Hermjakob, Henning
D'Eustachio, Peter
Saez-Rodriguez, Julio
Dopazo, Joaquin
Valencia, Alfonso
Kitano, Hiroaki
Barillot, Emmanuel
Auffray, Charles
Balling, Rudi
Schneider, Reinhard
Publisher :
Apollo - University of Cambridge Repository

Abstract

Funder: Bundesministerium f��r Bildung und Forschung<br />Funder: Bundesministerium f��r Bildung und Forschung (BMBF)<br />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.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........9e2c5fae73d35664df42208343a595ee