Discriminating microbial species using protein sequence properties and machine learning

Abstract

Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this assumption by comparing proteins and their properties from different bacterial species using Support Vector Machines (SVM). We show that by training on selected protein sequence properties, SVMs can successfully discriminate between proteins of different species. This finding takes us a step closer to inferring the functional characteristics of these proteins. © Springer-Verlag Berlin Heidelberg 2007.