DisGeNET: Difference between revisions

Revision as of 14:51, 30 July 2018

Latest revision as of 12:16, 14 May 2025

(9 intermediate revisions by 6 users not shown)

Line 1:

{{External links|date=January 2022}}

{{infobox biodatabase

|logo =

Line 11 ⟶ 12:

|standard =

|format =

|url = [https://www.disgenet.orgcom/ DisGeNETDISGENET]

|pmid = 25877637

|download = [http://www.disgenet.org/web/DisGeNET/menu/downloads Downloads]

Line 24 ⟶ 25:

|curation =

}}

'''DisGeNETDISGENET''' is a discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNETDISGENET is one of the largest and comprehensive repositories of human gene-disease associations (GDAs) currently available.<ref name=Pinero>{{cite journal|last1=Piñero|first1=J.|last2=Queralt-Rosinach|first2=N.|last3=Bravo|first3=A.|last4=Deu-Pons|first4=J.|last5=Bauer-Mehren|first5=A.|last6=Baron|first6=M.|last7=Sanz|first7=F.|last8=Furlong|first8=L. I.|title=DisGeNETDISGENET: a discovery platform for the dynamical exploration of human diseases and their genes|journal=Database|date=15 April 2015|volume=2015|issue=0|pages=bav028–bav028bav028|doi=10.1093/database/bav028|pmid=25877637|pmc=4397996}}</ref> It also offers a set of bioinformatic tools to facilitate the analysis of these data by different user profiles. It is maintained by the [http://ibi.imim.es/ Integrative Biomedical Informatics (IBI) Group] {{Webarchive|url=https://web.archive.org/web/20161126125258/http://ibi.imim.es/ |date=2016-11-26 }}, of the (GRIB)-IMIM/UPF, based at the [[Barcelona Biomedical Research Park]] (PRBB), Barcelona, [[Spain]].

==Scope and access==

In the pursuit to gather different aspects of the current knowledge on the genetic basis of human diseases, DisGeNETDISGENET 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, DisGeNETDISGENET is a valuable knowledge and evidence-based discovery resource for [[Translational Research]].

DisGeNETDISGENET is an open access resource that makes available a comprehensive knowledge base on disease genes and different tools for their exploitation and analysis. DisGeNETDISGENET is available through a [http://www.disgenet.orgcom/ 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|date=15 November 2010|volume=26|issue=22|pages=2924–6|doi=10.1093/bioinformatics/btq538|pmid=20861032|doi-access=free}}</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|last4=Mayer|first4=MA|last5=Sanz|first5=F|last6=Furlong|first6=LI|title=Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases.|journal=PLoSPLOS ONE|date=14 June 2011|volume=6|issue=6|pages=e20284|doi=10.1371/journal.pone.0020284|pmid=21695124|pmc=3114846|bibcode=2011PLoSO...620284B|doi-access=free}}</ref> and are designed to support the data exploitation from different perspectives and to fulfill the needs of different types of users, including bioinformaticians, biologists and healthcare practitioners.

==Integrated data==

The DisGeNETDISGENET 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="Bravo">{{cite journal|last1=Bravo|first1=À|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=21 February 2015|volume=16|issue=55|pagespage=1–3955|doi=10.1186/s12859-015-0472-9|pmid=25886734|pmc=4466840|doi-access=free}}</ref> The highlights of DisGeNETDISGENET 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 DisGeNETDISGENET 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 DisGeNETDISGENET Association Type Ontology==

For a seamless integration of gene-disease association data, we developed the DisGeNETDISGENET association type ontology. All association types as found in the original source databases are formally structured from a parent GeneDiseaseAssociation class if there is a relationship between the gene/protein and the disease, and represented as ontological classes. It is an OWL ontology that is integrated into the [http://code.google.com/p/semanticscience/wiki/SIO Sematicscience Integrated Ontology (SIO)], which provides essential types and relations for the rich description of objects, processes and their attributes.<ref name="Dumontier">{{cite journal|last1=Dumontier|first1=Michel|last2=Baker|first2=Christopher JO|last3=Baran|first3=Joachim|last4=Callahan|first4=Alison|last5=Chepelev|first5=Leonid|last6=Cruz-Toledo|first6=José|last7=Del Rio|first7=Nicholas R|last8=Duck|first8=Geraint|last9=Furlong|first9=Laura I|last10=Keath|first10=Nichealla|last11=Klassen|first11=Dana|last12=McCusker|first12=James P|last13=Queralt-Rosinach|first13=Núria|last14=Samwald|first14=Matthias|last15=Villanueva-Rosales|first15=Natalia|last16=Wilkinson|first16=Mark D|last17=Hoehndorf|first17=Robert|title=The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery|journal=Journal of Biomedical Semantics|date=2014|volume=5|issue=1|pages=14|doi=10.1186/2041-1480-5-14|pmc=4015691|pmid=24602174 |doi-access=free }}</ref> You can check SIO gene-disease association classes from this [http://semanticscience.org/resource/SIO_000983 URL].

==Cytoscape plugin==

The DisGeNETDISGENET Cytoscape plugin<ref name="Bauer" /> offers a network representation of the gene-disease associations. It represents gene-disease associations in terms of bipartite graphs and additionally provides gene centric and disease centric views of the data. It assists the user in the interpretation and exploration of human complex diseases with respect to their genetic origin by a variety of built-in functions. Using the DisGeNETDISGENET Cytoscape plugin you can perform queries restricted to (i) the original data source, (ii) the association type, (iii) the disorder class of interest and (iv) specific diseases or genes.

==Linked Data==

The information contained in DisGeNETDISGENET can also be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the [[Linked Open Data]] cloud. DisGeNETDISGENET is distributed as RDF and Nanopublications linked datasets. The DisGeNETDISGENET-RDF linked dataset is an alternative way to access the DisGeNETDISGENET data and provides new opportunities for data integration, querying and integrating DisGeNETDISGENET data to other external RDF datasets. The RDF and Nanopublication distributions of DisGeNETDISGENET have been developed in the context of [http://www.openphacts.org/ the Open PHACTS project] to provide disease relevant information to the knowledge base on pharmacological data.

==European projects==

Line 55 ⟶ 56:

{{reflist}}

[[Category:BiologicalGenetics databases]]