Similarity-based search of model organism, disease and drug effect phenotypes

Journal of Biomedical Semantics
Robert HoehndorfPaul N Schofield

Abstract

Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions, druggable therapeutic targets, and determination of pathogenicity. We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

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Citations

Jul 30, 2015·Genesis : the Journal of Genetics and Development·Prashanti MandaTodd J Vision
Jul 15, 2015·Mammalian Genome : Official Journal of the International Mammalian Genome Society·Susan M BelloJanan T Eppig
Nov 28, 2018·Journal of Cellular Physiology·Reyhaneh T EbdaliSamira Tabaei
Mar 29, 2018·Disease Models & Mechanisms·Susan M BelloLynn M Schriml
Sep 4, 2018·American Journal of Human Genetics·Toyofumi FujiwaraToshihisa Takagi

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Software Mentioned

OWLAPI
Phenomizer
ELK
PhenoDigm
ELK reasoner
Uberon
PhenomeNET
Monarch
simGIC
Semantic Measures Library ( SML )

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