结合支持向量机的基因表达特征分析

Analysis on Gene Expression Characteristics Combined with Support Vector Machine

基因表达特征分析是基因芯片的研究热点。在探讨基因表达特征分析框架的基础上,介绍基于统计学方法的特征基因选择,并构建支持向量分类器。一组白血病微阵列数据分析结果表明,获得的基因表达特征很好地体现了两种类型的白血病(AML和ALL)分子水平上的表达模式差异。

Gene expression characteristics analysis is the research hotspot of microarray. Based on discussing framework of gene expression characteristics analysis, the paper introduces the selection of the feature genes on basis of statistics method, and consturcts the support vector classifier. Through leukemia microarray data analysis the experimental results show that the gene expression characteristics obtained well reflects the differences in expression patterns at the molecular level between two leukemia types （AML and ALL） .