CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
01 06 2022
01 06 2022
Historique:
received:
01
09
2021
accepted:
26
04
2022
entrez:
1
6
2022
pubmed:
2
6
2022
medline:
7
6
2022
Statut:
epublish
Résumé
Since the outbreak of the COVID-19 pandemic, many research organizations have studied the genome of the SARS-CoV-2 virus; a body of public resources have been published for monitoring its evolution. While we experience an unprecedented richness of information in this domain, we also ascertained the presence of several information quality issues. We hereby propose CoV2K, an abstract model for explaining SARS-CoV-2-related concepts and interactions, focusing on viral mutations, their co-occurrence within variants, and their effects. CoV2K provides a clear and concise route map for understanding different connected types of information related to the virus; it thus drives a process of data and knowledge integration that aggregates information from several current resources, harmonizing their content and overcoming incompleteness and inconsistency issues. CoV2K is available for exploration as a graph that can be queried through a RESTful API addressing single entities or paths through their relationships. Practical use cases demonstrate its application to current knowledge inquiries.
Identifiants
pubmed: 35650205
doi: 10.1038/s41597-022-01348-9
pii: 10.1038/s41597-022-01348-9
pmc: PMC9160032
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
260Informations de copyright
© 2022. The Author(s).
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