Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.

ABSTRACT:

Background

Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms.

Results

We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large

SUBMITTER: Peng J 

PROVIDER: S-EPMC4339680 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature