Using path length measure for gene clustering based on similarity of annotation terms

Abstract

The application of semantic similarity measures on gene data using Gene Ontology (GO) and gene annotation information is becoming more widely used and acceptable in the recent years in bioinformatics. The purpose of this application can range from gene similarity to gene clustering. In this paper, we investigate a simple measure for gene similarity that relies on the path length between the GO annotation terms of genes to determine the similarity between them. The similarity values computed by the proposed measure for a set of genes will then be used for clustering the genes. In the evaluation, we compared the proposed measure with two widely used information-theoretic similarity measures, Resnik and Lin, using three datasets of genes. The experimental results and analysis of clusters validated the effectiveness of the proposed path length measure.