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 language | English (US) |
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Pages (from-to) | 201-209 |
Number of pages | 9 |
Journal | CEUR Workshop Proceedings |
Volume | 1766 |
State | Published - 2016 |
Event | 11th International Workshop on Ontology Matching, OM 2016 - Kobe, Japan Duration: Oct 18 2016 → … |
Bibliographical note
Publisher Copyright:© 2016, CEUR-WS. All rights reserved.
Keywords
- PhenomeNET
- Phenotype ontology
ASJC Scopus subject areas
- General Computer Science