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SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology.

Rashmie Abeysinghe1,2, Eugene W Hinderer3, Hunter N B Moseley3,4,5,6

  • 1School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.

Bioinformatics (Oxford, England)
|February 18, 2020
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Summary
This summary is machine-generated.

An automated framework, the Subsumption-based Sub-term Inference Framework (SSIF), identifies potentially missing Gene Ontology (GO) relations. This approach aids in improving the accuracy of biological knowledge organization.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Ontology Engineering

Background:

  • The Gene Ontology (GO) is a critical resource for standardizing biological knowledge.
  • Ensuring the quality of GO is essential to prevent misleading research outcomes.
  • Manual curation of GO for quality issues is increasingly difficult due to its scale.

Purpose of the Study:

  • To develop an automated method for detecting potential quality issues in the Gene Ontology.
  • To identify potentially missing is-a relationships within the GO structure.
  • To provide a scalable solution for auditing biological ontologies.

Main Methods:

  • Developed the Subsumption-based Sub-term Inference Framework (SSIF).
  • Utilized a novel term-algebra with a sequence-based representation of GO concepts.
  • Employed three conditional rules: monotonicity, intersection, and sub-concept rules.

Main Results:

  • SSIF identified 1938 potentially missing is-a relations in the GO database (October 3, 2018 release).
  • Domain expert evaluation of a sample demonstrated varying precision rates for the rules (e.g., 60.61% for monotonicity).
  • The framework offers a scalable approach to auditing complex biological ontologies.

Conclusions:

  • The automated auditing approach effectively suggests potentially missing relations in the Gene Ontology.
  • SSIF can assist in identifying and potentially correcting errors in biological knowledge bases.
  • This framework contributes to maintaining the integrity and utility of the Gene Ontology for biological research.