TY - JOUR T1 - Publishing DisGeNET as Nanopublications JF - bioRxiv DO - 10.1101/010397 SP - 010397 AU - NĂºria Queralt-Rosinach AU - Tobias Kuhn AU - Christine Chichester AU - Michel Dumontier AU - Ferran Sanz AU - Laura I. Furlong Y1 - 2014/01/01 UR - http://biorxiv.org/content/early/2014/10/16/010397.abstract N2 - 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. ER -