Parallel prediction of protein-protein interactions using proximal SVM

Abstract

In general, the interactions between proteins are fundamental to a broad area of biological functions. In this paper, we try to predict protein-protein interactions in parallel on a 12-node PC-cluster using domains of a protein. For this, we use a hydrophobicity among protein's amino acid's physicochemical feature and a support vector machine (SVM) among machine learning techniques. According to the experiments, we get approximately 60% average accuracy with 5 trials and we obtained an average speed-up of 5.11 with a 12-node cluster using a proximal SVM. © Springer-Verlag Berlin Heidelberg 2005.