Incorporating gene co-expression network in identification of cancer prognosis markers

Background: Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of high-throughput profiling technologies makes it possible to survey the whole genome and search for genomic markers with predictive power. Many existing studies assume the interchangeability of gene effects and ignore the coordination among them. Results: We adopt the weighted co-expression network to describe the interplay among genes. Although there are several different ways of defining gene networks, the weighted co-expression network may be preferred because of its computational simplicity, satisfactory empirical performance, and because it does not demand additional biological experiments. For cancer prognosis studies with gene expression measurements, we propose a new marker selection method that can properly incorporate the network connectivity of genes. We analyze six prognosis studies on breast cance...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Shuangge Ma, Mingyu Shi, Yang Li, Danhui Yi, Ben-Chang Shia
• Keywords: BMCBI 2010, Cancer, Predictive Power, Weighted Co-expression Network