Integrating phenotype ontologies with PhenomeNET

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

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

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 (US)
Pages (from-to)201-209
Number of pages9
JournalCEUR Workshop Proceedings
Volume1766
StatePublished - Jan 1 2016
Event11th International Workshop on Ontology Matching, OM 2016 - Kobe, Japan
Duration: Oct 18 2016 → …

Keywords

  • PhenomeNET
  • Phenotype ontology

ASJC Scopus subject areas

  • Computer Science(all)

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