DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

ABSTRACT: The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down the growth of such databases. We have addressed this problem by developing a text-mining system (DiMeX) to extract mutation to disease associations from publication abstracts. DiMeX consists of a series of natural language processing modules that preprocess input text and apply syntactic and semantic patterns to extract mutation-disease associations. DiMeX achieves high precision and recall with F-scores of 0.88, 0.91 and 0.89 when evaluated on three different datasets for mutation-disease associations. DiMeX includes a separate component that ex

SUBMITTER: Mahmood AS 

PROVIDER: S-EPMC4830514 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature