COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms
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BiBTeXWe 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.
SEEK ID: https://publications.h-its.org/publications/1291
Research Groups: Scientific Databases and Visualisation
Publication type: Journal
Journal: Molecular Systems Biology
Citation: Molecular Systems Biology 17(10),e10387
Date Published: 1st Oct 2021
Registered Mode: by DOI
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SubmitterViews: 4411
Created: 25th Oct 2021 at 11:31
Last updated: 5th Mar 2024 at 21:24
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Research Groups: Scientific Databases and Visualisation
Institutions: Heidelberg Institute for Theoretical Studies
https://orcid.org/0000-0002-8683-7084
Research Groups: Scientific Databases and Visualisation, Computational Molecular Evolution, Physics of Stellar Objects, Molecular and Cellular Modeling, Molecular Biomechanics, Astroinformatics, Groups and Geometry, Playground, Computational Carbon Chemistry, Data Mining and Uncertainty Quantification, Computational Statistics, SIMPLAIX
Institutions: Heidelberg Institute for Theoretical Studies, Heidelberg University
Research Groups: Scientific Databases and Visualisation, Astroinformatics, Data Mining and Uncertainty Quantification, Groups and Geometry, Natural Language Processing, Computational Molecular Evolution, Computational Carbon Chemistry, Physics of Stellar Objects, Playground, Molecular and Cellular Modeling, Stellar Evolution Theory, SIMPLAIX
Institutions: Heidelberg Institute for Theoretical Studies
Public web page: https://sdbv.h-its.org
