TY - JOUR
AU - Ostaszewski, Marek
AU - Niarakis, Anna
AU - Mazein, Alexander
AU - Kuperstein, Inna
AU - Phair, Robert
AU - Orta-Resendiz, Aurelio
AU - Singh, Vidisha
AU - Aghamiri, Sara Sadat
AU - Acencio, Marco Luis
AU - Glaab, Enrico
AU - Ruepp, Andreas
AU - Fobo, Gisela
AU - Montrone, Corinna
AU - Brauner, Barbara
AU - Frishman, Goar
AU - Gómez, Luis Cristóbal Monraz
AU - Somers, Julia
AU - Hoch, Matti
AU - Gupta, Shailendra Kumar
AU - Scheel, Julia
AU - Borlinghaus, Hanna
AU - Czauderna, Tobias
AU - Schreiber, Falk
AU - Montagud, Arnau
AU - de Leon, Miguel Ponce
AU - Funahashi, Akira
AU - Hiki, Yusuke
AU - Hiroi, Noriko
AU - Yamada, Takahiro G.
AU - Dräger, Andreas
PY - 2021
DA - October
TI - COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
JO - Molecular Systems Biology
VL - 17
IS - 10
DO - https://doi.org/10.15252/msb.202110387
AB - 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.
PB - Embopress
UR - https://www.research.ed.ac.uk/en/publications/957c1e9f-10d1-4eea-b49a-e2f593488cf1
KW - Coronavirus (COVID-19)
KW - Digital health and technology
ER