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

Eighteen months of COVID-19 pandemic
in my blog.

Just read the paper (doi:10.15252/msb.202110387).

Abstract

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.

The beauty of open science is that people want to collaborate, open licensing makes this simpler, and magic happens. We just published magic. Of course, it's not done, and keeping up with literature turned out to be a problem. After the shock in February/March 2020 of the pandemic (yes, I know many were still in denial), the time I could afford to keep up got less and less. Normal life had to return. Thanks to everyone involved and particularly for Anna and Marek for herding the cats.