A New Nonparametric Gene Selection Method for Classification of Microarray Data
Gene selection is a central step of gene expression data analysis.In this paper, a new nonparametric method, Gene Selection for Multiclass (GSM), is proposed, which selects genes based on the criterion of the large inter-class difference and the small intra-class difference. Using the default training and testing sets on two publicly available datasets, leukemia (two classes) and SRBCT(four classes), the proposed method has been evaluated and compared with three relative methods, F-test, SAM and cho. The experimental results show GSM is effective and robust to select differential expression genes.
Gene selection Gene Selection for Multiclass large inter-class difference small intra-class difference
Lihua Ye Yonggang Li Kun Yang
Computer Application Research Lab Jiaxing University Jiaxing 314001, China School of Computer Hangzhou Dianzi University Hangzhou 310018, China
国际会议
第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)
南京
英文
1928-1933
2009-07-25（万方平台首次上网日期，不代表论文的发表时间）