DisGeNET: Difference between revisions

Revision as of 08:41, 16 August 2015

Revision as of 08:57, 16 August 2015

Line 30:

==Scope and access==

In the pursuit to gather different aspects of the current knowledge on the genetic basis of human diseases, DisGeNET covers information on all disease areas (Mendelian, complex and environmental diseases). With more than 400 000 genotype-phenotype relationships from different origins integrated and annotated with explicit provenance and evidence information, DisGeNET is a valuable knowledge and evidence-based discovery resource for [[Translational Research]].

DisGeNET is an open access resource that makes available a comprehensive knowledge base on disease genes and different tools for their exploitation and analysis. DisGeNET is available through a [http://www.disgenet.org/ Web interface], a [[Cytoscape]] plugin,<ref name="Bauer">{{cite journal|last1=Bauer-Mehren|first1=A|last2=Rautschka|first2=M|last3=Sanz|first3=F|last4=Furlong|first4=LI|title=DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks.|journal=Bioinformatics (Oxford, England)|date=15 November 2010|volume=26|issue=22|pages=2924–6|doi=10.1093/bioinformatics/btq538|pmid=20861032}}</ref> as [[linked data]] for the Semantic Web, and supports programmatic access to its data. These valuable set of tools allows investigating the molecular mechanisms underlying diseases of genetic origin, <ref name="Bauer2">{{cite journal|last1=Bauer-Mehren|first1=A|last2=Bundschus|first2=M|last3=Rautschka|first3=M|last3last4=Mayer|first3first4=MA|last4last5=Sanz|first4first5=F|last5last6=Furlong|first5first6=LI|title=Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases.|journal=PLoS ONE|date=14 June 2011|volume=6|issue=6|pages=2924–6|doi=10.1371/journal.pone.0020284}}</ref> and are designed to support the data exploitation from different perspectives and to fulfil the needs of different types of users, including bioinformaticians, biologists and healthcare practitioners.

==Integrated data==

The DisGeNET database integrates over 400 000 associations between > 17 000 genes and > 14 000 diseases from human to animal model expert curated databases with text mined GDAs from MEDLINE using a NLP-based approach.<ref name="befree">{{cite journal|last1=Bravo|first1=A|last2=Piñero|first2=J|last3=Queralt-Rosinach|first3=N|last4=Rautschka|first4=M|last5=Furlong|first5=LI|title=Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.|journal=BMC Bioinformatics|date=14 June 2011|volume=6|issue=6|pages=2924–6|doi=10.1186/s12859-015-0472-9}</ref> The highlights of DisGeNET are the data integration, standardisation and a fine-grained tracking of the provenance information. The integration is performed by means of gene and disease vocabulary mapping and by using the DisGeNET association type ontology. Furthermore, GDAs are organised according to their type and level of evidence as CURATED, PREDICTED and LITERATURE, and they are also scored based on the supporting evidence to prioritise and ease their exploration.

==The DisGeNET Association Type Ontology==