COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
Ostaszewski, Marek ; Marchesi, Silvia LU
and Schneider, Reinhard
(2021)
In Molecular Systems Biology
17(10).
- 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... (More)
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.
(Less)
- author
- Ostaszewski, Marek
; Marchesi, Silvia
LU
and Schneider, Reinhard
- author collaboration
- publishing date
- 2021-10
- type
- Contribution to journal
- publication status
- published
- keywords
- Antiviral Agents/therapeutic use, COVID-19/genetics, Computational Biology/methods, Computer Graphics, Cytokines/genetics, Data Mining/statistics & numerical data, Databases, Factual, Gene Expression Regulation, Host Microbial Interactions/genetics, Humans, Immunity, Cellular/drug effects, Immunity, Humoral/drug effects, Immunity, Innate/drug effects, Lymphocytes/drug effects, Metabolic Networks and Pathways/genetics, Myeloid Cells/drug effects, Protein Interaction Mapping, SARS-CoV-2/drug effects, Signal Transduction, Software, Transcription Factors/genetics, Viral Proteins/genetics, COVID-19 Drug Treatment
- in
- Molecular Systems Biology
- volume
- 17
- issue
- 10
- article number
- e10387
- publisher
- EMBO Press
- external identifiers
-
- scopus:85118262224
- pmid:34664389
- ISSN
- 1744-4292
- DOI
- 10.15252/msb.202110387
- language
- English
- LU publication?
- no
- additional info
- © 2021 The Authors. Published under the terms of the CC BY 4.0 license.
- id
- 8e764d80-1bba-4326-a0fb-df3bc6af347a
- date added to LUP
- 2025-03-10 08:24:26
- date last changed
- 2025-07-01 21:12:26
@article{8e764d80-1bba-4326-a0fb-df3bc6af347a,
abstract = {{<p>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.</p>}},
author = {{Ostaszewski, Marek and Marchesi, Silvia and Schneider, Reinhard}},
issn = {{1744-4292}},
keywords = {{Antiviral Agents/therapeutic use; COVID-19/genetics; Computational Biology/methods; Computer Graphics; Cytokines/genetics; Data Mining/statistics & numerical data; Databases, Factual; Gene Expression Regulation; Host Microbial Interactions/genetics; Humans; Immunity, Cellular/drug effects; Immunity, Humoral/drug effects; Immunity, Innate/drug effects; Lymphocytes/drug effects; Metabolic Networks and Pathways/genetics; Myeloid Cells/drug effects; Protein Interaction Mapping; SARS-CoV-2/drug effects; Signal Transduction; Software; Transcription Factors/genetics; Viral Proteins/genetics; COVID-19 Drug Treatment}},
language = {{eng}},
number = {{10}},
publisher = {{EMBO Press}},
series = {{Molecular Systems Biology}},
title = {{COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms}},
url = {{http://dx.doi.org/10.15252/msb.202110387}},
doi = {{10.15252/msb.202110387}},
volume = {{17}},
year = {{2021}},
}