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The COVID-19 Ontology.

Astghik Sargsyan1,2, Alpha Tom Kodamullil1, Shounak Baksi3

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

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Summary

A new COVID-19 ontology aids research by organizing SARS-CoV-2 data. This tool supports text mining and drug repurposing for COVID-19 therapeutics development.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Medical Informatics

Background:

  • The COVID-19 pandemic spurred global academic collaboration.
  • A need exists for structured data to support text mining and harmonization for COVID-19 research.
  • Drug repurposing is a key strategy in COVID-19 therapeutic development.

Purpose of the Study:

  • To develop a comprehensive ontology for novel coronavirus (SARS-CoV-2) entities.
  • To focus the ontology on chemical entities relevant to drug repurposing.
  • To facilitate data description, linking, and harmonization in the context of COVID-19.

Main Methods:

  • Development of a formal ontology representing SARS-CoV-2 related concepts.
  • Inclusion of molecular, cellular, medical, and epidemiological entities.
  • Testing the ontology's performance on Medline and a specialized COVID-19 corpus.

Main Results:

  • The COVID-19 Ontology includes 2270 classes and 38,987 axioms.
  • It details virus-host interactions, viral life cycle, and COVID-19-related medical concepts.
  • Ontology performance was validated using established biomedical corpora.

Conclusions:

  • The developed ontology provides a structured framework for COVID-19 research.
  • It supports text mining, data integration, and drug repurposing efforts.
  • The ontology is publicly available for broad scientific use.