DocumentCode :
2039361
Title :
Comprehensive analyses of tumor suppressor genes in protein-protein interaction networks: A topological perspective
Author :
Min Zhao ; Jingchun Sun ; Zhongming Zhao
Author_Institution :
Dept. of Biomed. Inf., Vanderbilt Univ., Nashville, TN, USA
fYear :
2012
fDate :
2-4 Dec. 2012
Firstpage :
101
Lastpage :
102
Abstract :
Tumor suppressor genes (TSGs) are a class of genes that play key roles in cancer induction and development. A comprehensive investigation of TSGs in protein-protein interaction (PPI) networks may expand our understanding on their roles in cancer development. In this study, we first collected reliable human TSG lists from tumor suppressor gene database. To provide an unbiased network view, we mapped human TSGs to four model organisms with different evolutionary distances to human (mouse, fly, worm, and yeast) using homology relationship. Using human TSGs and their homologs, we overlapped TSGs to their corresponding PPI networks. To explore the network properties of TSGs we examined their degree, betweenness, and closeness centralities by uniquely comparing them with three other sets of genes. We found that TSGs tend to interact more strongly than other non-cancer disease genes in human, mouse, fly, and worm, which confirmed previous global topological property studies on cancer genes. This demonstrates that TSGs are important to initiate interaction with other molecular during cancer development. This study represents the first statistical evaluation of TSGs in PPI networks. In addition, the data presented in this study will be valuable for the study of TSGs and their interaction partners.
Keywords :
bioinformatics; cancer; evolution (biological); genetics; molecular biophysics; proteins; statistical analysis; topology; tumours; PPI networks; and closeness centrality; betweenness centrality; cancer development; cancer induction; evolutionary distances; fly; homology relationship; model organisms; mouse; noncancer disease genes; protein-protein interaction networks; statistical evaluation; tumor suppressor genes; worm; yeast; Global network characteristics; Network topology; Protein-protein interaction; Tumor suppressor gene;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genomic Signal Processing and Statistics, (GENSIPS), 2012 IEEE International Workshop on
Conference_Location :
Washington, DC
ISSN :
2150-3001
Print_ISBN :
978-1-4673-5234-5
Type :
conf
DOI :
10.1109/GENSIPS.2012.6507738
Filename :
6507738
Link To Document :
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