Identification of missing hierarchical relations in the vaccine ontology using acquired term pairs.

Journal: Journal of biomedical semantics
PMID: 35964149

Abstract

BACKGROUND: The Vaccine Ontology (VO) is a biomedical ontology that standardizes vaccine annotation. Errors in VO will affect a multitude of applications that it is being used in. Quality assurance of VO is imperative to ensure that it provides accurate domain knowledge to these downstream tasks. Manual review to identify and fix quality issues (such as missing hierarchical is-a relations) is challenging given the complexity of the ontology. Automated approaches are highly desirable to facilitate the quality assurance of VO.

Authors

  • Warren Manuel
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Rashmie Abeysinghe
    Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Yongqun He
    University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA.
  • Cui Tao
    The University of Texas Health Science Center at Houston, USA.
  • Licong Cui
    The University of Texas Health Science Center at Houston, USA.

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