Information theory applied to the sparse gene ontology annotation network to predict novel gene function.

ABSTRACT:

Motivation

Despite advances in the gene annotation process, the functions of a large portion of gene products remain insufficiently characterized. In addition, the in silico prediction of novel Gene Ontology (GO) annotations for partially characterized gene functions or processes is highly dependent on reverse genetic or functional genomic approaches. To our knowledge, no prediction method has been demonstrated to be highly accurate for sparsely annotated GO terms (those associated to fewer than 10 genes).

Results

We propose a novel approach, information theory-based semantic similarity (ITSS), to automatically predict molecular functions of genes based on existing GO annotations. Using a 10-fold cross-validation, we demonstrate that the ITSS algorithm obtains prediction acc

SUBMITTER: Tao Y 

PROVIDER: S-EPMC2882681 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature