Professor Robert Hoehndorf's PhenomeNET method wins at Ontology matching workshop

2016-10-23 - 10:29

artificial intelligence
bioinformatics
biomedical data
PhenomeNET

-By Rose Gregorio

Professor Robert Hoehndorf and Postdoctoral Fellow Miguel Angel Rodriguez Garcia are the winners of the Ontology Alignment Evaluation Initiative Challenge sponsored by Pistoia Alliance.

PhenomeNET is a cross-species phenotype network. The latest release (June 2013) contains 124,730 complex phenotype nodes taken from yeast, fish, worm, fly, rat, slime mold and mouse model organism databases as well as human disease phenotypes from OMIM and OrphaNet.

The network is a complete graph in which edge weights represent the degree of phenotypic similarity which can be used to identify and prioritize candidate disease genes, find genes participating in the same pathway and orthologous genes between species.

Hoehndorf presented his research in the Ontology Matching Workshop that is co-located with ISWC 2016 in Kobe, Japan.

View the official announcement.