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基于基因灵敏度信息和二进制微粒群优化的基因选择方法
  • 摘要

    为了得到低冗余度高识别率的基因子集,提出了一种耦合基因灵敏度信息的微粒群优化基因选择方法.首先,通过单隐层神经网络从微阵列数据中提取各个基因的基因—类别灵敏度值;其次,在基因聚类基础上,利用基因灵敏度信息滤除低灵敏度的基因;最后,将基因灵敏度信息编码进二进制微粒群优化算法作进一步基因选择.在两个公开的微阵列数据集上的实验结果表明,对比其他方法,由于充分考虑各个基因灵敏度信息,因此能够选出较少基因但分类性能更高的基因子集.

  • 作者

    孙伟  韩飞  SUN Wei  HAN Fei 

  • 作者单位

    江苏大学计算机科学与通信工程学院,江苏镇江,212013

  • 刊期

    2014年9期 ISTIC PKU

  • 关键词

    基因选择  基因灵敏度  二进制微粒群优化  微阵列数据  gene selection  gene-to-class sensitivity  binary particle swarm optimization  microarray data 

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