Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database.

ABSTRACT: The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be r

SUBMITTER: Davis AP 

PROVIDER: S-EPMC3629079 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature