A new method for measuring the semantic similarity on gene ontology

Abstract

Semantic similarity defined on Gene Ontology (GO) aims to provide the functional relationship between different biological processes, molecular functions, or cellular components. In this paper, a novel method, namely the Shortest Path (SP) algorithm, for measuring the semantic similarity on GO is proposed based on both the GO structure information and the term's property. The proposed algorithm searches for the shortest path that connects two terms and uses the sum of weights on the shortest path to compute the semantic similarity for GO terms. A method for evaluating the nonlinear correlation between two variables is also introduced for validation. Extensive experiments conducted on two public gene expression datasets demonstrate the overall superiority of SP method over the other state-of-the-art methods evaluated.