Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

Provenance-Centered Dataset of Drug-Drug Interactions

Preprint

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.

      Related collections

      Author and article information

      Journal
      20 July 2015
      1507.05408

      http://arxiv.org/licenses/nonexclusive-distrib/1.0/

      Custom metadata
      In Proceedings of the 14th International Semantic Web Conference (ISWC) 2015
      cs.CY

      Comments

      Comment on this article