NAR Molecular Biology Database Collection entry number 1914
Piñero, Janet; Bravo, Àlex; Queralt-Rosinach, Núria; Gutiérrez-Sacristán, Alba; Deu-Pons, Jordi; Centeno, Emilio; García-García, Javier; Sanz, Ferran; Furlong, Laura I.
Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, C/Dr Aiguader 88, E-08003 Barcelona, Spain

Database Description

DisGeNET is a knowledge platform that contains one of the largest available collections of genes and variants involved in human diseases. It 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. As of October 2016, DisGeNET (v4.0) contains 429,036 associations, between 17,381 genes and 15,093 diseases, disorders and clinical or abnormal human phenotypes, and 72,870 variant-disease associations (VDAs), between 46,589 SNPs and 6,356 diseases and phenotypes.


Instituto de Salud Carlos III-Fondo Europeo de Desarrollo Regional [CP10/00524 and PI13/00082]; the Innovative Medicines Initiative Joint Undertaking [Open PHACTs No. 115191], resources of which are composed of financial contribution from the European Union's Seventh Framework Programme [FP7/2007-2013] and EFPIA companies’ in kind contribution; the European Union Horizon 2020 Programme 2014–2020 [MedBioinformatics No. 634143 and Elixir-Excelerate No. 676559]. The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023, of the PE I+D+i 2013-2016, funded by ISCIII and FEDER.


1. Piñero, J., Queralt-Rosinach, N., Bravo, À., Deu-Pons, J., Bauer-Mehren, A., Baron, M., Sanz, and Furlong L.I. (2015) DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database, Apr 15;2015:bav028.
2. Queralt-Rosinach, N, Piñero, J, Bravo, À, Sanz, F., and Furlong, L.I. (2016) DisGeNET-RDF: Harnessing the Innovative Power of the Semantic Web to Explore the Genetic Basis of Diseases. Bioinformatics, Jul 15;32(14):2236-8.
3. Bauer-Mehren, A, Bundschus, M, Rautschka, M, Mayer, M.A., Sanz, F., and Furlong, L.I (2011) Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases. PLoS ONE, 6(6):e20284, doi:10.1371/journal.pone.0020284
4. Bauer-Mehren A, Rautschka M, Sanz F, and Furlong L.I. (2010) DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks. Bioinformatics, Nov 15;26(22):2924-6.

Go to the abstract in the NAR 2017 Database Issue.
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