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


Ostaszewski M., Niarakis A., Mazein A., Kuperstein I., Phair R., Orta-Resendiz A., ...Daha Fazla

MOLECULAR SYSTEMS BIOLOGY, cilt.17, sa.10, 2021 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 10
  • Basım Tarihi: 2021
  • Doi Numarası: 10.15252/msb.202110387
  • Dergi Adı: MOLECULAR SYSTEMS BIOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, EMBASE, MEDLINE, Directory of Open Access Journals
  • Anahtar Kelimeler: computable knowledge repository, large-scale biocuration, omics data analysis, open access community effort, systems biomedicine, NF-KAPPA-B, INTERFERON SIGNALING PATHWAY, SPIKE PROTEIN, SARS-COV, CORONAVIRUS, EXPRESSION, SARS-COV-2, BETA, DEGRADATION, ENVIRONMENT
  • Ankara Üniversitesi Adresli: Evet

Özet

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.