DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases

Motivation: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is int...

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Detalles Bibliográficos
Autores principales: Queralt-Rosinach, Núria, Piñero, Janet, Bravo, Àlex, Sanz, Ferran, Furlong, Laura I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937199/
https://www.ncbi.nlm.nih.gov/pubmed/27153650
http://dx.doi.org/10.1093/bioinformatics/btw214
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author Queralt-Rosinach, Núria
Piñero, Janet
Bravo, Àlex
Sanz, Ferran
Furlong, Laura I.
author_facet Queralt-Rosinach, Núria
Piñero, Janet
Bravo, Àlex
Sanz, Ferran
Furlong, Laura I.
author_sort Queralt-Rosinach, Núria
collection PubMed
description Motivation: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. Availability and implementation: http://rdf.disgenet.org/ Contact: support@disgenet.org
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spelling pubmed-49371992016-07-11 DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases Queralt-Rosinach, Núria Piñero, Janet Bravo, Àlex Sanz, Ferran Furlong, Laura I. Bioinformatics Applications Notes Motivation: DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. Availability and implementation: http://rdf.disgenet.org/ Contact: support@disgenet.org Oxford University Press 2016-07-15 2016-03-22 /pmc/articles/PMC4937199/ /pubmed/27153650 http://dx.doi.org/10.1093/bioinformatics/btw214 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Queralt-Rosinach, Núria
Piñero, Janet
Bravo, Àlex
Sanz, Ferran
Furlong, Laura I.
DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title_full DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title_fullStr DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title_full_unstemmed DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title_short DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases
title_sort disgenet-rdf: harnessing the innovative power of the semantic web to explore the genetic basis of diseases
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937199/
https://www.ncbi.nlm.nih.gov/pubmed/27153650
http://dx.doi.org/10.1093/bioinformatics/btw214
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