Ferran Sanz | bioRxiv Science

bioRxiv2015

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

MotivationDisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web (SW). 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 (LOD).\n\nAvailabilityhttp://rdf.disgenet.org/\n\nContactsupport@disgenet.org

Bioinformatics↗

bioRxiv2014

Publishing DisGeNET as Nanopublications

The increasing and unprecedented publication rate in the biomedical field is a major bottleneck for discovery in Life Sciences. The scientific community cannot process assertions from biomedical publications and integrate them into the current knowledge at the same rate. The automatic extraction of assertions about entities and their relationships by text-mining the scientific literature is an extended approach to structure up-to-date knowledge. For knowledge integration, the publication of assertions in the Semantic Web is gaining adoption, but it opens new challenges regarding the tracking of the provenance, and how to ensure versioned data linking. Nanopublications are a new way of publishing structured data that consists of an assertion along with its provenance. Trusty URIs is a novel approach to make resources in the Web immutable, and to ensure the unambiguity of the data linking in the (semantic) Web. We present the publication of DisGeNET nanopublications as a new Linked Dataset implemented in combination of the Trusty URIs approach. DisGeNET is a database of human gene-disease associations from expert-curated databases and text-mining the scientific literature. With a series of illustrative queries we demonstrate its utility.

Bioinformatics↗