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DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must b...

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Autores principales: Piñero, Janet, Bravo, Àlex, Queralt-Rosinach, Núria, Gutiérrez-Sacristán, Alba, Deu-Pons, Jordi, Centeno, Emilio, García-García, Javier, Sanz, Ferran, Furlong, Laura I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210640/
https://www.ncbi.nlm.nih.gov/pubmed/27924018
http://dx.doi.org/10.1093/nar/gkw943
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author Piñero, Janet
Bravo, Àlex
Queralt-Rosinach, Núria
Gutiérrez-Sacristán, Alba
Deu-Pons, Jordi
Centeno, Emilio
García-García, Javier
Sanz, Ferran
Furlong, Laura I.
author_facet Piñero, Janet
Bravo, Àlex
Queralt-Rosinach, Núria
Gutiérrez-Sacristán, Alba
Deu-Pons, Jordi
Centeno, Emilio
García-García, Javier
Sanz, Ferran
Furlong, Laura I.
author_sort Piñero, Janet
collection PubMed
description The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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spelling pubmed-52106402017-01-05 DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants Piñero, Janet Bravo, Àlex Queralt-Rosinach, Núria Gutiérrez-Sacristán, Alba Deu-Pons, Jordi Centeno, Emilio García-García, Javier Sanz, Ferran Furlong, Laura I. Nucleic Acids Res Database Issue The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance. Oxford University Press 2017-01-04 2016-10-19 /pmc/articles/PMC5210640/ /pubmed/27924018 http://dx.doi.org/10.1093/nar/gkw943 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Piñero, Janet
Bravo, Àlex
Queralt-Rosinach, Núria
Gutiérrez-Sacristán, Alba
Deu-Pons, Jordi
Centeno, Emilio
García-García, Javier
Sanz, Ferran
Furlong, Laura I.
DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title_full DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title_fullStr DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title_full_unstemmed DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title_short DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
title_sort disgenet: a comprehensive platform integrating information on human disease-associated genes and variants
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210640/
https://www.ncbi.nlm.nih.gov/pubmed/27924018
http://dx.doi.org/10.1093/nar/gkw943
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