A stable gene selection in microarray data analysis |
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| Authors: | Kun Yang Zhipeng Cai Jianzhong Li Guohui Lin |
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| Institution: | (1) Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China;(2) Department of Computing Science, University of Alberta, Edmonton, Alberta, T6G 2E8, Canada |
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| Abstract: | Background Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples.
Gene selection is to detect the most significantly differentially expressed genes under different conditions, and it has been
a central research focus. In general, a better gene selection method can improve the performance of classification significantly.
One of the difficulties in gene selection is that the numbers of samples under different conditions vary a lot. |
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