关键词: 基因表达谱, 特征基因, 肿瘤诊断, 支持向量机

Abstract: Gene selection for cancer diagnosis method based on gene expression profile has become a hot topic in diagnosing cancer cells.However，the high dimensionality，small sample set and many noises of gene expression data make this task challenging.Thus，a novel gene selection method is provided.Firstly，use the ratio of interval gap or intersection cover to the whole span to select some discriminative genes，and then take use of an efficient procedure to cut off the redundancy genes in order to get higher accuracy and fewer genes.Finally，use three datasets to demonstrate the efficiency of the method.Using the 5-fold cross-validation method，only two or three genes can reach 100% accuracy in cancer classification.Compared with other cancer classification methods，it shows the competitive results.

Key words: gene expression, feature gene, cancer diagnosis, support vector machine