Protein Interaction Network Prediction and Pathways Analyses Related Atherosclerosis

• Published in: 2011 5th International Conference on Bioinformatics and Biomedical Engineering pp. 1 - 4
• Main Authors: Shanshan Gu, Zhenyang Li, Wenlong Lai, Yang Zeng, Xuan Si, Jianwei Wang, Quhuan Li
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2011
• Subjects: Atherosclerosis; Bioinformatics; Cancer; Diseases; Proteins
• ISBN: 9781424450886; 1424450888
• ISSN: 2151-7614; 2151-7622
• DOI: 10.1109/icbbe.2011.5780048

Atherosclerosis is a complex pathophysiological condition characterized by lipid accumulation in the vascular wall and regulated by multiple genetic and environmental factors. To better understand molecular modulation mechanism involving various molecules and complex pathways, an efficient bioinformatics approach was introduced to construct a protein interaction network related to atherosclerosis. In this study, Genes and proteins were collected from nucleotide database, a biological interaction network was constructed using the BOND database, the topological characteristics of the modulated protein pathway-related were analyzed with Cytoscape, and the biological process were classified based on KEGG database. Our results indicate 350 genes were relevant with atherosclerosis, 3142 nodes and 4012 interactions were included in a high confidence network, a series of key gene with large degree were identified, 124 biological pathways were found out. To sum up, an integrated interaction network was constructed, and the topological analyses of the protein network was carried out. These results enabled us to identify a set of candidate proteins, which would be the potential promising targets for new drug and efficacious prevention.