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The COVID-19 Ontology.
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.
  • Sargsyan A; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Kodamullil AT; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Baksi S; Causality Biomodels, Kinfra Hi-Tech Park, Kalamassery, Cochin, India Kerala.
  • Darms J; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Madan S; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Gebel S; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Keminer O; Fraunhofer Institute for Molecular Biology and Applied Ecology-ScreeningPort, Hamburg, Germany.
  • Jose GM; Causality Biomodels, Kinfra Hi-Tech Park, Kalamassery, Cochin, India Kerala.
  • Balabin H; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • DeLong LN; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Kohler M; Fraunhofer Institute for Molecular Biology and Applied Ecology-ScreeningPort, Hamburg, Germany.
  • Jacobs M; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
  • Hofmann-Apitius M; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
Bioinformatics ; 2020 Dec 21.
Article in English | MEDLINE | ID: covidwho-2303118
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 2.270 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.

AVAILABILITY:

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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Bioinformatics

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Bioinformatics