Title :
Identification of lung cancer associated protein by clique percolation clustering analysis
Author :
Kurubanjerdjit, Nilubon ; Chien-Hung Huang ; Ka-Lok Ng
Author_Institution :
Dept. of Biomed. Inf., Asia Univ., Taichung, Taiwan
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.
Keywords :
cancer; genetics; lung; medical computing; patient diagnosis; pattern clustering; proteins; proteomics; cancer cellular network; cancer genes; cancer proteins; cancer research; clique motif; clique percolation clustering analysis; clique percolation clustering approach; enriched KEGG pathways; enriched protein biological function; gene ontology annotation; lung cancer associated protein identification; lung cancer protein-protein interaction information; molecular network; topological network; Biological processes; Cancer; Communities; Databases; Lungs; Protein engineering; Proteins; clique network; enrichment analysis; lung cancer; oncogene; protein-protein interaction; tumor suppressor gene;
Conference_Titel :
Communications and Information Technologies (ISCIT), 2013 13th International Symposium on
Conference_Location :
Surat Thani
Print_ISBN :
978-1-4673-5578-0
DOI :
10.1109/ISCIT.2013.6645951
