Show simple item record

dc.contributor.authorHoehndorf, Robert
dc.contributor.authorGruenberger, Michael
dc.contributor.authorGkoutos, Georgios V
dc.contributor.authorSchofield, Paul N
dc.date.accessioned2015-03-16T05:26:14Z
dc.date.available2015-03-16T05:26:14Z
dc.date.issued2015-02-19
dc.identifier.citationSimilarity-based search of model organism, disease and drug effect phenotypes 2015, 6 (1) Journal of Biomedical Semantics
dc.identifier.issn2041-1480
dc.identifier.pmid25763178
dc.identifier.doi10.1186/s13326-015-0001-9
dc.identifier.urihttp://hdl.handle.net/10754/346698
dc.description.abstractBackground: 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. Results: 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. Conclusions: 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.
dc.publisherSpringer Science + Business Media
dc.relation.urlhttp://www.jbiomedsem.com/content/6/1/6
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.titleSimilarity-based search of model organism, disease and drug effect phenotypes
dc.typeArticle
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalJournal of Biomedical Semantics
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDepartment of Computer Science, Aberystwyth University
dc.contributor.institutionDepartment of Physiology, Development & Neuroscience, University of Cambridge
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personHoehndorf, Robert
kaust.personHoehndorf, Robert
refterms.dateFOA2018-06-14T04:42:21Z


Files in this item

Thumbnail
Name:
s13326-015-0001-9.pdf
Size:
336.3Kb
Format:
PDF
Description:
Main article

This item appears in the following Collection(s)

Show simple item record