TopoICSim: a new semantic similarity measure based on gene ontology.

ABSTRACT:

Background

The Gene Ontology (GO) is a dynamic, controlled vocabulary that describes the cellular function of genes and proteins according to tree major categories: biological process, molecular function and cellular component. It has become widely used in many bioinformatics applications for annotating genes and measuring their semantic similarity, rather than their sequence similarity. Generally speaking, semantic similarity measures involve the GO tree topology, information content of GO terms, or a combination of both.

Results

Here we present a new semantic similarity measure called TopoICSim (Topological Information Content Similarity) which uses information on the specific paths between GO terms based on the topology of the GO tree, and the distribution of information

SUBMITTER: Ehsani R 

PROVIDER: S-EPMC4966780 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature