Large-scale reasoning over functions in biomedical ontologies

Robert Hoehndorf*, Liam Mencel, Georgios V. Gkoutos, Paul N. Schofield

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A large number of biomedical resources have been developed to represent the functions of biological entities, and these resources are widely used for data integration and analysis. Expressing functions in biomedical ontologies currently uses formal representation patterns that renders basic reasoning tasks to fall in complexity classes beyond polynomial time, thereby limiting the potential of using knowledge-based methods for data integration, querying or quality control. Here, we propose an alternative representation pattern for expressing knowledge about biological functions, together with a biological and ontological justification, which can be expressed using the description logic EL++ and implemented using the OWL 2 EL profile. To demonstrate the utility of our account of biological functions, we apply it to all proteins contained in the SwissProt database and evaluate its utility with respect to answering complex queries as well with respect to the classification and query times.

Original languageEnglish (US)
Title of host publicationFormal Ontology in Information Systems - Proceedings of the 9th International Conference, FOIS 2016
EditorsRoberta Ferrario, Werner Kuhn
PublisherIOS Press
Pages299-312
Number of pages14
ISBN (Electronic)9781614996590
DOIs
StatePublished - Jan 1 2016
Event9th Formal Ontology in Information Systems Conference, FOIS 2016 - Annecy, France
Duration: Jul 6 2016Jul 9 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume283
ISSN (Print)0922-6389

Other

Other9th Formal Ontology in Information Systems Conference, FOIS 2016
CountryFrance
CityAnnecy
Period07/6/1607/9/16

Keywords

  • Big ontologies
  • Biological function
  • Protein
  • Tractable reasoning

ASJC Scopus subject areas

  • Artificial Intelligence

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