DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes

被引:691
作者
Pinero, Janet [1 ]
Queralt-Rosinach, Nuria [1 ]
Bravo, Alex [1 ]
Deu-Pons, Jordi [1 ]
Bauer-Mehren, Anna [2 ]
Baron, Martin [3 ]
Sanz, Ferran [1 ]
Furlong, Laura I. [1 ]
机构
[1] Univ Pompeu Fabra, Dept Expt & Hlth Sci, Hosp Mar Med Res Inst IMIM, Res Programme Biomed Informat GRIB, E-08003 Barcelona, Spain
[2] Roche Diagnost GmbH, Roche Innovat Ctr Penzberg, Roche Pharma Res & Early Dev, pRED Informat, D-82377 Penzberg, Germany
[3] Roche Diagnost GmbH, Sci & Business Informat Serv, D-82377 Penzberg, Germany
来源
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION | 2015年
关键词
DATABASE; KNOWLEDGE; ONTOLOGY; POLYMORPHISMS; EXTRACTION; GENOTYPES; MEDICINE; BIOLOGY; PANTHER; MODEL;
D O I
10.1093/database/bav028
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380 000 associations between >16 000 genes and 13 000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners.
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页数:17
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