Work

Integrating phenotype ontologies with PhenomeNET

Year: 2016

Type: conference-paper

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.

Source: University of Birmingham Research Portal (University of Birmingham)

Authors: García, Miguel Angel Rodríguez, Gkoutos, Georgios V.; id_orcid 0000-0002-2061-091X, Schofield, Paul N., Hoehndorf, Robert

Institutions: King Abdullah University of Science and Technology, University of Cambridge

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

Open Access status: green

OpenAlex ID: W2583127320

FWCI: 0.939

Cites: 14

Cited by: 4

Related to: 10