TmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine.

ABSTRACT:

Motivation

Despite significant efforts in expert curation, clinical relevance about most of the 154 million dbSNP reference variants (RS) remains unknown. However, a wealth of knowledge about the variant biological function/disease impact is buried in unstructured literature data. Previous studies have attempted to harvest and unlock such information with text-mining techniques but are of limited use because their mutation extraction results are not standardized or integrated with curated data.

Results

We propose an automatic method to extract and normalize variant mentions to unique identifiers (dbSNP RSIDs). Our method, in benchmarking results, demonstrates a high F-measure of ∼90% and compared favorably to the state of the art. Next, we applied our approach to the entire

SUBMITTER: Wei CH 

PROVIDER: S-EPMC5860583 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature