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Similarity-based search of model organism, disease and drug effect phenotypes
BACKGROUND: 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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355138/ https://www.ncbi.nlm.nih.gov/pubmed/25763178 http://dx.doi.org/10.1186/s13326-015-0001-9 |
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author | Hoehndorf, Robert Gruenberger, Michael Gkoutos, Georgios V Schofield, Paul N |
author_facet | Hoehndorf, Robert Gruenberger, Michael Gkoutos, Georgios V Schofield, Paul N |
author_sort | Hoehndorf, Robert |
collection | PubMed |
description | BACKGROUND: 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. |
format | Online Article Text |
id | pubmed-4355138 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43551382015-03-12 Similarity-based search of model organism, disease and drug effect phenotypes Hoehndorf, Robert Gruenberger, Michael Gkoutos, Georgios V Schofield, Paul N J Biomed Semantics Software BACKGROUND: 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. BioMed Central 2015-02-19 /pmc/articles/PMC4355138/ /pubmed/25763178 http://dx.doi.org/10.1186/s13326-015-0001-9 Text en © Hoehndorf et al.; licensee BioMed Central. 2015 This 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. |
spellingShingle | Software Hoehndorf, Robert Gruenberger, Michael Gkoutos, Georgios V Schofield, Paul N Similarity-based search of model organism, disease and drug effect phenotypes |
title | Similarity-based search of model organism, disease and drug effect phenotypes |
title_full | Similarity-based search of model organism, disease and drug effect phenotypes |
title_fullStr | Similarity-based search of model organism, disease and drug effect phenotypes |
title_full_unstemmed | Similarity-based search of model organism, disease and drug effect phenotypes |
title_short | Similarity-based search of model organism, disease and drug effect phenotypes |
title_sort | similarity-based search of model organism, disease and drug effect phenotypes |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355138/ https://www.ncbi.nlm.nih.gov/pubmed/25763178 http://dx.doi.org/10.1186/s13326-015-0001-9 |
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