Title: Gene identification and survival prediction with Lp Cox regression and novel similarity measure
Authors: Zhenqiu Liu, Feng Jiang
Addresses: University of Maryland Greenebaum Cancer, Center, 22 South Greene Street, Baltimore, MD 21201, USA. ' University of Maryland Greenebaum Cancer, Center, 22 South Greene Street, Baltimore, MD 21201, USA
Abstract: In this paper, Cox|s proportional hazards model with Lp penalty method is developed for simultaneous gene selection and survival prediction. Lp penalty shrinks coefficients and produces some coefficients that are exactly zero, and therefore can be used to identify survival related downstream genes. We also define a novel similarity measure to hunt the regulatory genes that their gene expression changes may be low but they are highly correlated with the selected genes. Experimental results with gene expression data demonstrate that the proposed procedures can be used for identifying important gene clusters that are related to time to death due to cancer and for building parsimonious model for predicting the survival of future patients.
Keywords: survival prediction; gene selection; L2 penalty; gene identification; bioinformatics; proportional hazards model; gene expression data; gene clusters; cancer survival; patient survival.
International Journal of Data Mining and Bioinformatics, 2009 Vol.3 No.4, pp.398 - 408
Published online: 09 Nov 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article