Text Mining Genotype-Phenotype Relationships from Biomedical Literature for Database Curation and Precision Medicine.

ABSTRACT: The practice of precision medicine will ultimately require databases of genes and mutations for healthcare providers to reference in order to understand the clinical implications of each patient's genetic makeup. Although the highest quality databases require manual curation, text mining tools can facilitate the curation process, increasing accuracy, coverage, and productivity. However, to date there are no available text mining tools that offer high-accuracy performance for extracting such triplets from biomedical literature. In this paper we propose a high-performance machine learning approach to automate the extraction of disease-gene-variant triplets from biomedical literature. Our approach is unique because we identify the genes and protein products associated with each mutation from

SUBMITTER: Singhal A 

PROVIDER: S-EPMC5130168 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature