基于模糊自适应共振网络简化模型方法的乳腺肿瘤基因分类

上海大学学报(自然科学版)

基于模糊自适应共振网络简化模型方法的乳腺肿瘤基因分类

陈志宏，严壮志，刘书朋

上海大学通信与信息工程学院，上海 200072

收稿日期:2005-07-15 修回日期:1900-01-01 出版日期:1900-01-01 发布日期:1900-01-01
通讯作者: 严壮志

Classification of Breast Cancer Genes with a Simplified Fuzzy ARTMAP Approach

CHEN Zhi-hong,YAN Zhuang-zhi,LIU Shu-peng

School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China

Received:2005-07-15 Revised:1900-01-01 Online:1900-01-01 Published:1900-01-01
Contact: YAN Zhuang-zhi

摘要/Abstract

摘要：

以乳腺肿瘤的基因微阵列实验所产生的基因微阵列表达数据为研究对象，针对大规模基因表达模式分析的特点，提出基于模糊自适应共振网络简化模型的基因表达数据分类方法，并在此基础上实现了BRCA1变异和BRCA2变异的乳腺肿瘤分类.利用Hedenfalk的基因微阵列数据，对BRCA1变异和BRCA2变异作分类计算，计算结果达到78%以上的正确率.

关键词: 基因表达数据, 模糊自适应共振网络简化模型, 遗传性乳腺肿瘤

Abstract:

This paper presents a gene expression-based classification method for hereditary breast cancer, using a simplified fuzzy ART map. The method was tested on gene expression profiles with BRCA1 and BRCA2, respectively, from Hedenfalk's experiment. The results show that the method has a hit rate of 78% estimated by leave one out method.

Key words: gene expression data, SFAM, hereditary breast cancer

中图分类号:

Q 332

陈志宏;严壮志;刘书朋. 基于模糊自适应共振网络简化模型方法的乳腺肿瘤基因分类[J]. 上海大学学报(自然科学版).

CHEN Zhi-hong;YAN Zhuang-zhi;LIU Shu-peng. Classification of Breast Cancer Genes with a Simplified Fuzzy ARTMAP Approach[J]. Journal of Shanghai University（Natural Science Edition）.