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Gene selection method using neural networks and genetic algorithm and its applications to classification of cancers

  • 조현성 (인하대학교 정보통신공학과) ;
  • 김태선 (가톨릭대학교 컴퓨터.전자공학부) ;
  • 전성모 (인하대학교 정보통신공학과) ;
  • 위재우 (인하대학교 정보통신공학과) ;
  • 이종호 (인하대학교 정보통신공학과)
  • Cho, Hyun-Sung (School of Computer Science and Electronic Engineering) ;
  • Kim, Tae-Seon (Catholic Univ. of Korea) ;
  • Jeon, Sung-Mo (School of Computer Science and Electronic Engineering) ;
  • Wee, Jae-Woo (School of Computer Science and Electronic Engineering) ;
  • Lee, Chong-Ho (School of Computer Science and Electronic Engineering)
  • 발행 : 2002.07.10

초록

Classification method of cancers using cDNA microarrays data was developed using genetic algorithms and neural networks. For gene selection, 2308 genes were ranked using genetic algorithms, and selected by frequency number of selection from 1000 of genetic iterative runs. To calculate fitness values, artificial neural networks are used as classifier. The small, round blue cell tumors (SRBCTs) which is difficult to distinguish via pathological single test was used as test diseases for classification, and the test results showed the 96% of exact classification capability for 25 test samples.

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