Datamining with ontologies

Robert Hoehndorf, Georgios V. Gkoutos, Paul N. Schofield

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

7 Scopus citations

Abstract

The use of ontologies has increased rapidly over the past decade and they now provide a key component of most major databases in biology and biomedicine. Consequently, datamining over these databases benefits from considering the specific structure and content of ontologies, and several methods have been developed to use ontologies in datamining applications. Here, we discuss the principles of ontology structure, and datamining methods that rely on ontologies. The impact of these methods in the biological and biomedical sciences has been profound and is likely to increase as more datasets are becoming available using common, shared ontologies.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages385-397
Number of pages13
DOIs
StatePublished - Aug 1 2016

Publication series

NameMethods in Molecular Biology
Volume1415
ISSN (Print)1064-3745

Keywords

  • Automated reasoning
  • Data integration
  • Enrichment
  • Graph algorithms
  • Ontology
  • Semantic Web
  • Semantic similarity
  • Web Ontology Language (OWL)

ASJC Scopus subject areas

  • Genetics
  • Molecular Biology

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