Identification of lung cancer associated protein by clique percolation clustering analysis

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 protei...

Full description

Saved in:
Bibliographic Details
Main Authors: Kurubanjerdjit, Nilubon, Chien-Hung Huang, Ka-Lok Ng
Format: Conference Proceeding
Language:English
Subjects:
Biological processes
Cancer
clique network
Communities
enrichment analysis
lung cancer
Lungs
oncogene
Protein engineering
protein-protein interaction
Proteins
tumor suppressor gene
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
DOI:10.1109/ISCIT.2013.6645951