DocumentCode
3703453
Title
Weighted gene coexpression network analysis of prostate cancer
Author
Yinjiao Ma;Lingling Zhang;Christian Geneus;Haijun Gong
Author_Institution
Department of Biostatistics, Saint Louis University, St. Louis, MO, USA
fYear
2015
Firstpage
1
Lastpage
6
Abstract
Population-based cohort studies found that the incidence and mortality rates of prostate cancer in the African Americans are more than double of other races in the United States. Some socioeconomic and environmental factors can not fully explain this health disparity among different populations. The pathogenesis of prostate cancer is characterized by some genetic mutations and deregulated signaling pathways. Understanding the gene modules or networks could help us elucidate the mechanisms and causes underlying this racial disparity in prostate cancer. In this work, we applied a weighted gene coexpression network analysis method to analyze the microarray data of prostate cancer sampled from different races. Our studies reveal several gene modules that are not preserved in the prostate cancer progression, and also identify some modules specific to the African American and white American patients.
Keywords
"Prostate cancer","Heuristic algorithms","Topology","Genetics","Network topology","Diseases"
Publisher
ieee
Conference_Titel
Computational Advances in Bio and Medical Sciences (ICCABS), 2015 IEEE 5th International Conference on
Type
conf
DOI
10.1109/ICCABS.2015.7344728
Filename
7344728
Link To Document