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. 2015 Apr 15:2015:bav028.
doi: 10.1093/database/bav028. Print 2015.

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

Janet Piñero  1 , Núria Queralt-Rosinach  1 , Àlex Bravo  1 , Jordi Deu-Pons  1 , Anna Bauer-Mehren  1 , Martin Baron  1 , Ferran Sanz  1 , Laura I Furlong  2
Affiliations

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

Janet Piñero et al. Database (Oxford). .

Abstract

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. Database URL: http://www.disgenet.org/

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Figures

Figure 1.
Figure 1.
The main features of the DisGeNET discovery platform. DisGeNET is available through a web interface, a Cytoscape plugin, as a Semantic Web resource, and supports programmatic access to its data.
Figure 2.
Figure 2.
Venn diagrams showing the overlaps among genes, diseases and GDAs according to their source. LITERATURE corresponds to GAD, BeFree and LHGDN.
Figure 3.
Figure 3.
Distribution of DisGeNET genes by Panther protein class (a), and by Reactome pathways (b). Note that for both classifications, we used the top-level class.
Figure 4.
Figure 4.
Distribution of diseases and genes according to the MeSH disease classification.
Figure 5.
Figure 5.
The DisGeNET association type ontology.
Figure 6.
Figure 6.
The two entry points to the web interface: the Search view (a) and the Browse view (b).
Figure 7.
Figure 7.
Simplified data model of the DisGeNET RDF representation.
Figure 8.
Figure 8.
Highlights of the information that can be extracted from DisGeNET, using PPARG as example. (a) Selection of the diseases associated to PPARG, with the number of data sources supporting them. N: Number of genes annotated to the disease with score higher than or equal to PPARG. P: Number of articles supporting the association. (b) Distribution of scores by disease class, for the 42 diseases reported by curated sources. Only classes with more than one disease are shown. The number of disease terms in each class is shown on the top of the x-axis. (c) Examples of PPARG relations to a selection of diseases. The networks were obtained with the DisGeNET Cytoscape plugin. The colors of edges reflect different association types.
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