The COVID-19 Ontology

Abstract Motivation The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel cor...

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Published inBioinformatics Vol. 36; no. 24; pp. 5703 - 5705
Main Authors Sargsyan, Astghik, Kodamullil, Alpha Tom, Baksi, Shounak, Darms, Johannes, Madan, Sumit, Gebel, Stephan, Keminer, Oliver, Jose, Geena Mariya, Balabin, Helena, DeLong, Lauren Nicole, Kohler, Manfred, Jacobs, Marc, Hofmann-Apitius, Martin
Format Journal Article Web Resource
LanguageEnglish
Published England Oxford University Press 05.04.2021
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Summary:Abstract Motivation The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel coronavirus (SARS-CoV-2) entities. The ontology has a strong scope on chemical entities suited for drug repurposing, as this is a major target of ongoing COVID-19 therapeutic development. Results The ontology comprises 2270 classes of concepts and 38 987 axioms (2622 logical axioms and 2434 declaration axioms). It depicts the roles of molecular and cellular entities in virus-host interactions and in the virus life cycle, as well as a wide spectrum of medical and epidemiological concepts linked to COVID-19. The performance of the ontology has been tested on Medline and the COVID-19 corpus provided by the Allen Institute. Availabilityand implementation COVID-19 Ontology is released under a Creative Commons 4.0 License and shared via https://github.com/covid-19-ontology/covid-19. The ontology is also deposited in BioPortal at https://bioportal.bioontology.org/ontologies/COVID-19. Supplementary information Supplementary data are available at Bioinformatics online.
Bibliography:The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btaa1057