An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics

Matthias Samwald, Robert Freimuth, Joanne S. Luciano, Simon Lin, Robert L. Powers, M. Scott Marshall, Klaus Peter Adlassnig, Michel Dumontier, Richard D. Boyce

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Pages539-542
Number of pages4
Edition1-2
ISBN (Print)9781614992882
DOIs
StatePublished - 2013
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
Number1-2
Volume192
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other14th World Congress on Medical and Health Informatics, MEDINFO 2013
Country/TerritoryDenmark
CityCopenhagen
Period8/20/138/23/13

Keywords

  • Pharmacogenetics
  • clinical decision support systems
  • medical informatics
  • ontology
  • pharmacogenomics

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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