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作者:

Xiaogang, Ruan (Xiaogang, Ruan.) | Jinlian, Wang (Jinlian, Wang.) | Hui, Li (Hui, Li.)

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摘要:

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. © 2007 IEEE.

关键词:

Feature extraction Gene expression Genetic algorithms RNA Support vector machines Tabu search Tumors

作者机构:

  • [ 1 ] [Xiaogang, Ruan]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Jinlian, Wang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 3 ] [Hui, Li]College of Computer of Science and Technology, Beijing University of Techonology, Beijing, China

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年份: 2007

页码: 234-237

语种: 英文

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WoS核心集被引频次: 0

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