换一批摘要We propose a new, method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis (ICA). Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to classify the modeling data. To show the validity of the proposed method, we applied it to classify three DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.
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分类号
Q5（生物化学）
栏目名称
发布时间
2008-12-17（万方平台首次上网日期，不代表论文的发表时间）
基金项目
the National Natural Science Foundation of China（(30700161)）
the National High-Tech Research and Development Program (863 Program)
of China（(2007AA01Z167 and 2006AA02Z309)）
China Postdoctoral Science Foundation（(20070410223)）
Doctor Scientific Research Startup Foundation of Qufu Normal University（(Bsqd2007036)）
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