摘要: DNA微阵列技术使人们可同时观测成千上万个基因的表达水平,对其数据的分析已成为生物信息学研究的焦点。针对微阵列基因表达数据维数高、样本小、非线性的特点,设计并实现了一种基因表达数据分类识别方法,针对结肠数据集的实验表明其泛化效果有所增强。
关键词:
DNA微阵列,
基因表达谱,
神经网络集成,
负相关学习,
反向传播算法
Abstract: Based on DNA microarray experiment, the expression level of thousands of genes can be observed simultaneously, and the method of the anlysis is focused in bioinformatics. Because microarray gene expression data is high dimensions and small samples and non-line, a method of gene expression data anlysis is put forward. The method has been successfully applied to the colon gene expression data set and got enhanced generalization performance .
中图分类号:
刘青,周鹏. 基于强泛化神经网络的大规模基因表达数据分析[J]. , 2005, 31(03): 193-195.
LIU Qing1,2, ZHOU Peng2. Data Analysis of Cosmically Microarray Gene Expression Based on Neural Networks with Enhanced Generalization[J]. , 2005, 31(03): 193-195.