Incremental data integration for tracking genotype-disease associations.

ABSTRACT: Functional annotation of genes remains a challenge in fundamental biology and is a limiting factor for translational medicine. Computational approaches have been developed to process heterogeneous data into meaningful metrics, but often do not address how findings might be updated when new evidence comes to light. To address this challenge, we describe requirements for a framework for incremental data integration and propose an implementation based on phenotype ontologies and Bayesian probability updates. We apply the framework to quantify similarities between gene annotations and disease profiles. Within this scope, we categorize human diseases according to how well they can be recapitulated by animal models and quantify similarities between human diseases and mouse models produced by the

SUBMITTER: Konopka T 

PROVIDER: S-EPMC7004389 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature