Identification of lung cancer associated protein by clique percolation clustering analysis

Abstract

Identification of cancer associated proteins is the crucial problem in cancer research. Recently various techniques have been developed to discover novel cancer genes/proteins. Topological network of protein-protein interaction with their gene ontology annotation are good predictors of cancer proteins. Protein-protein interaction information has provided a basis for studying the cancer cellular network. In this study, we implemented clique percolation clustering approach on lung cancer protein-protein interaction information to identify cancer associated proteins, the enriched protein biological function in molecular networks of the clique motif and also the enriched KEGG pathways were observed.