Using computational predictions to improve literature-based Gene Ontology annotations: a feasibility study.

ABSTRACT: Annotation using Gene Ontology (GO) terms is one of the most important ways in which biological information about specific gene products can be expressed in a searchable, computable form that may be compared across genomes and organisms. Because literature-based GO annotations are often used to propagate functional predictions between related proteins, their accuracy is critically important. We present a strategy that employs a comparison of literature-based annotations with computational predictions to identify and prioritize genes whose annotations need review. Using this method, we show that comparison of manually assigned 'unknown' annotations in the Saccharomyces Genome Database (SGD) with InterPro-based predictions can identify annotations that need to be updated. A survey of literat

SUBMITTER: Costanzo MC 

PROVIDER: S-EPMC3067894 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature