A Novel Method to Detect Functional Subgraphs in Biomolecular Networks

Abstract

A NOVEL METHOD TO DETECT FUNCTIONAL SUBGRAPHS IN BIOMOLECULAR NETWORKS Sterling Wells Thomas, Doctor of Philosophy A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University Virginia Commonwealth University, 2010 Danail Bonchev, Ph.D., Sc.D., Senior Fellow, Professor and Director of Research on Bioinformatics, Center for the Study of Biological Complexity Several biomolecular pathways governing the control of cellular processes have been discovered over the last several years. Additionally, advances resulting from combining these pathways into networks have produced new insights into the complex behaviors observed in cell function assays. Unfortunately, identification of important sub-networks, or “motifs”, in these networks has been slower in development. This study focused on identifying important network motifs and their rate of occurrence in two different biomolecular networks. The two networks evaluated for this study represented both ends of the spectrum of interaction knowledge by comparing a well defined network (apoptosis) with and poorly studied network that was early in development (autism). This study identified several motifs that could be important in governing and controlling cellular processes in healthy and diseased cells. Additionally, this study revealed an inverse relationship when comparing the occurrence rate of these motifs in apoptosis and autism.