scholarly journals Independent component analysis of Alzheimer's DNA microarray gene expression data

2009 ◽  
Vol 4 (1) ◽  
pp. 5 ◽  
Author(s):  
Wei Kong ◽  
Xiaoyang Mou ◽  
Qingzhong Liu ◽  
Zhongxue Chen ◽  
Charles R Vanderburg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Independent Component Analysis ◽  
Dna Microarray ◽  
Gene Expression Data ◽  
Component Analysis ◽  
Microarray Gene Expression Data ◽  
Independent Component ◽  
Expression Data ◽  
Microarray Gene Expression ◽  
Microarray Gene

TUMOR CLASSIFICATION BASED ON INDEPENDENT COMPONENT ANALYSIS

2006 ◽  
Vol 20 (02) ◽  
pp. 297-310 ◽  
Author(s):  
CHUN-HOU ZHENG ◽  
YAN CHEN ◽  
XIU-XIA LI ◽  
YI-XUE LI ◽  
YUN-PING ZHU
Keyword(s):  
Gene Expression ◽  
Independent Component Analysis ◽  
Dna Microarray ◽  
Gene Expression Data ◽  
Component Analysis ◽  
Tumor Classification ◽  
Independent Component ◽  
Support Vector ◽  
Expression Data ◽  
Microarray Gene Expression

This paper proposes a new method for tumor classification using gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are selected using t-statistics. Secondly, the selected genes are modeled by Independent Component Analysis (ICA). Finally, Support Vector Machine (SVM) is used to classify the modeling data. To show the validity of the proposed method, we apply it to classify two DNA microarray data sets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.

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