An Intelligent Search Algorithm for Feature Gene Selection of Chinese Gastric Cancer with mRNA Microarray Data
An intelligent algorithm based on genetic algorithm search for selecting an optimal gene subset was presented and applied it to the Chinese gastric cancer mRNA microarray data to discover the feature genes. Firstly, an improved genetic algorithm was proposed to learn the optimal subsets of genes.Then a support vector machine (SVM) was employed to find the gene subset with best classification performance for distinguishing cancerous tissues and their counterparts. Some of the obtained feature genes have been validated by Beijing Molecular Oncology Laboratory. Both of the biological and computational experiments have shown that the improved genetic algorithm has good performance in both the quality of obtained feature subsets and computation efficiency.
Feature gene selection SVM genetic algorithm Chinese gastric cancer
Xiaogang Ruan Jinlian wang Hui Li
College of Electronic Information and Control Engineering Beijing University of Technology Beijing, College of Computer of Science and Technology Beijing University of Techonology Beijing, China
国际会议
武汉
英文
238-241
2007-07-06（万方平台首次上网日期，不代表论文的发表时间）