By Topic

Differential Gene Expression Analysis on Microarray Data of Breast Cancer Based on Subgroup Statistic Methods

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Ji Zhaohua ; Dept. of Commun. Eng., Jilin Univ., Changchun, China ; Liu Fu ; Wang Yao ; Shi Xiaohu
more authors

Tomlins et al. (2005) found that the differential expressed genes might only exist in a subset of the cancer group, rather than in all samples of the group. From then on, lots of methods have been proposed by considering this point. In this paper, we first surveyed the recent research progress of detection methods for differential gene expression (DGE) in micro array data of cancer subgroup, and then applied six commonly used methods to simulated data and database provided by West. Through analyzing experimental results, we compared the performance of the six detection methods. This paper performs a comprehensive comparison study of currently popular detection methods of differential gene expression for micro array data analysis with regard to over-expressed cancer subgroup. The obtained results are helpful for dealing with micro array data using detection methods.

Published in:

Biomedical Engineering and Biotechnology (iCBEB), 2012 International Conference on

Date of Conference:

28-30 May 2012