Graph Theory Analysis of Protein-Protein Interaction Network and Graph based Clustering of Proteins linked with Zika Virus using MCL Algorithm

摘要

Graph mining is an advancing region notably to dig up unique and intuitiveness facts from data that is pictured as a graph. Graph data like protein-protein interaction network is pervasive in actuality so that graph theory means of analysis to network can advantage supplementary findings of proteins associated with positive topological characteristic have precise biological function. Distinct graph mining techniques such as frequent subgraph mining, clustering, classification is feasible to figure out the protein-protein interaction networks. Clustering is one of the well-known technique to boast a class of proteins with related biological function. Some of the graph based clustering methods include local neighborhood density search method, flow simulation method and population based stochastic search method. MCL algorithm based on flow simulation method over protein-protein interaction network of proteins related zika virus has been analytically gauged and indicated how interesting clusters are raised.