The COVID-19 Ontology

Author:

Sargsyan Astghik12ORCID,Kodamullil Alpha Tom1,Baksi Shounak3,Darms Johannes1,Madan Sumit1,Gebel Stephan1,Keminer Oliver4,Jose Geena Mariya3,Balabin Helena1,DeLong Lauren Nicole1,Kohler Manfred4,Jacobs Marc1,Hofmann-Apitius Martin12

Affiliation:

1. Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), 53754 Sankt Augustin, Germany

2. Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53113 Bonn, Germany

3. Causality Biomodels, Kinfra Hi-Tech Park, Cochin, Kerala 683503, India

4. Fraunhofer Institute for Molecular Biology and Applied Ecology-ScreeningPort, Hamburg, Germany

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.

Funder

MAVO program

Fraunhofer Society

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference7 articles.

1. Repurposing of clinically approved drugs for treatment of coronavirus disease 2019 in a 2019-novel coronavirus (2019-nCoV) related coronavirus model;Fan;Chin. Med. J. (Engl.),2020

2. Early dynamics of transmission and control of COVID-19: a mathematical modelling studyLancet;Kucharski;Infect Dis,2020

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