Integrating phenotype ontologies with PhenomeNET

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

Authors

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

External organisations

  • King Abdullah University of Science and Technology
  • University of Cambridge

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.

Details

Original languageEnglish
Title of host publicationOM 2016 - Ontology Matching
Subtitle of host publicationProceedings of the 11th International Workshop on Ontology Matching
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
CountryJapan
CityKobe
Period18/10/1618/10/16

Keywords

  • PhenomeNET, Phenotype ontology

ASJC Scopus subject areas