Integrating phenotype ontologies with PhenomeNET

Miguel Angel Rodríguez García, Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf

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

3 Citations (Scopus)
135 Downloads (Pure)

Abstract

PhenomeNET is a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Here, we apply the PhenomeNET to identify related classes from four phenotype and disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone.

Original languageEnglish
Title of host publicationOM 2016 - Ontology Matching
Subtitle of host publicationProceedings of the 11th International Workshop on Ontology Matching
PublisherCEUR
Pages201-209
Number of pages9
Volume1766
Publication statusPublished - 22 Dec 2016
EventThe Eleventh International Workshop on Ontology Matching - Kobe, Japan
Duration: 18 Oct 201618 Oct 2016

Publication series

NameCEUR Workshop Proceedings
Volume1766
ISSN (Print)1613-0073

Conference

ConferenceThe Eleventh International Workshop on Ontology Matching
Abbreviated titleOM-2016
Country/TerritoryJapan
CityKobe
Period18/10/1618/10/16

Keywords

  • PhenomeNET
  • Phenotype ontology

ASJC Scopus subject areas

  • Computer Science(all)

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