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 in	Bioinformatics 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
Language	English
Published	England Oxford University Press 05.04.2021
Subjects	Applications Notes
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Abstract	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.
AbstractList	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. 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. 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. 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 data are available at Bioinformatics online.
Author	DeLong, Lauren Nicole Kodamullil, Alpha Tom Keminer, Oliver Gebel, Stephan Kohler, Manfred Madan, Sumit Balabin, Helena Hofmann-Apitius, Martin Baksi, Shounak Jose, Geena Mariya Sargsyan, Astghik Jacobs, Marc Darms, Johannes
AuthorAffiliation	btaa1057-aff1 Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) , 53754 Sankt Augustin, Germany btaa1057-aff3 Causality Biomodels, Kinfra Hi-Tech Park , Cochin, Kerala 683503, India btaa1057-aff2 Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn , 53113 Bonn, Germany btaa1057-aff4 Fraunhofer Institute for Molecular Biology and Applied Ecology-ScreeningPort , Hamburg, Germany
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References	Zhao (2023062408125196700_btaa1057-B7) 2020; 8 (2023062408125196700_btaa1057-B1) 2020 Jin (2023062408125196700_btaa1057-B3) 2020 Smith (2023062408125196700_btaa1057-B5) 2020 Fan (2023062408125196700_btaa1057-B2) 2020 Kucharski (2023062408125196700_btaa1057-B4) 2020 Ton (2023062408125196700_btaa1057-B6) 2020; 39
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Title	The COVID-19 Ontology
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