Ontology based text mining of gene-phenotype associations: application to candidate gene prediction.

ABSTRACT: Gene-phenotype associations play an important role in understanding the disease mechanisms which is a requirement for treatment development. A portion of gene-phenotype associations are observed mainly experimentally and made publicly available through several standard resources such as MGI. However, there is still a vast amount of gene-phenotype associations buried in the biomedical literature. Given the large amount of literature data, we need automated text mining tools to alleviate the burden in manual curation of gene-phenotype associations and to develop comprehensive resources. In this study, we present an ontology-based approach in combination with statistical methods to text mine gene-phenotype associations from the literature. Our method achieved AUC values of 0.90 and 0.75 in re

SUBMITTER: Kafkas S 

PROVIDER: S-EPMC6391585 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature