Datamining with Ontologies

Robert Hoehndorf, Georgios V Gkoutos, Paul N Schofield

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

6 Citations (Scopus)

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
Title of host publicationProtocol: Data Mining Techniques for the Life Sciences
PublisherSprinter
Pages385-397
Number of pages13
ISBN (Print)978-1-4939-3570-3
DOIs
Publication statusPublished - 27 Apr 2016

Publication series

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

Keywords

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

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