Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes.

ABSTRACT: Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in

SUBMITTER: Saunders CJ 

PROVIDER: S-EPMC4726433 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature