GOGO: An improved algorithm to measure the semantic similarity between gene ontology terms.

ABSTRACT: Measuring the semantic similarity between Gene Ontology (GO) terms is an essential step in functional bioinformatics research. We implemented a software named GOGO for calculating the semantic similarity between GO terms. GOGO has the advantages of both information-content-based and hybrid methods, such as Resnik's and Wang's methods. Moreover, GOGO is relatively fast and does not need to calculate information content (IC) from a large gene annotation corpus but still has the advantage of using IC. This is achieved by considering the number of children nodes in the GO directed acyclic graphs when calculating the semantic contribution of an ancestor node giving to its descendent nodes. GOGO can calculate functional similarities between genes and then cluster genes based on their functional

SUBMITTER: Zhao C 

PROVIDER: S-EPMC6180005 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature