关键词: 肿瘤, 基因表达谱, 特征基因, 特征选取, 神经网络

Abstract: Building an effective classification model based on gene expression profiles is of great importance in tumor diagnosing and its clinical therapy.To the classification problem of tumor subtype，finding a group of gene subsets that are relevant to tumor subtype is a crucial task.The author propose a novel gene selection method that firstly adopt Relief-F algorithm to remove the genes that are irrelevant to tumor subtype and then adopt K-means algorithm to remove redundant genes.The author apply Artificial Neural Networks（ANN）to evaluating the classification ability of the selected gene subset.Experiments on the pediatric acute lymphoblastic leukemia dataset that contains seven tumor subtypes show that 100% cross-validated accuracy rate can be obtained by ANN classifier，which prove that the proposed method is very effective in multi-class tumor subtypes recognition.

Key words: tumor, gene expression profiles, informative gene, feature selection, neural networks