Study of Node Arrival in Evolution of Disease Network

Abstract

Protein-protein interaction network(PPI) is a biological network which represents interaction between proteins and these interactions change over time. Our aim is to study how these networks change from normal state to disease state. The normal network transforms into a disease network by new proteins joining the network or existing proteins leaving the network. To model this process, Graph kernel measures are used. By comparing pairs of graphs with different arrival sequences of nodes, we try to discover the arrival sequence that produces a smooth transition during transformation of a normal network into a disease network. Also the nodes that produce significant changes in the network are studied from the perspective of influential nodes theory in social networks. The network evolution is modelled using Duplication-mutation with complementarity (DMC) model. Results at a global level matching of network properties are satisfactory. But the actual matching of links between the simulated network and the original is poor and this issue needs to be investigated further.