A functional annotation based integration of different similarity measures for gene expressions

Abstract

Genes with similar expression profiles often exhibit similar functional properties. An "integrated similarity score" (ISS) is developed by combining different expression similarity measures through weights, obtained using biological information, for improving gene similarity. The expression similarity measures are converted to the common framework of positive predictive value using functional annotation. A fitness function, called "fitness function using functional annotation of genes" (FFFAG), is also developed by minimizing the difference between functional similarity value and the ISS. The FFFAG is used to determine the weight combination of different similarity measures in ISS. In addition, an existing similarity measure, called TMJ (integrated similarity measure by multiplying Triangle and Jaccard similarity), is also modified to incorporate biological knowledge involving functional annotation. The results demonstrate that ISS is superior to individual similarity measure to find similar gene pairs. Further, the ISS predicts the functional categories of 40 unclassified yeast genes at p-value cutoff of 10-10 from 12 clusters. The associated code is accessible at http://www.isical.ac.in/[~]shubhra/ISS.html.