中文

Journal of Applied Sciences ›› 2012, Vol. 30 ›› Issue (3): 287-293.doi: 10.3969/j.issn.0255-8297.2012.03.012

• Signal and Information Processing • Previous Articles     Next Articles

Molecular Classification of Acute Leukemia Using EHW with Filter-Based Gene Selection

WANG Jin1;3, DING Ling1, SUN Kai-wei1, LEE Chong-ho2   

  1. 1. College of Computer Science and Technology, Chongqing University of Posts and
    Telecommunications, Chongqing 400065, China
    2. Department of Information and Communication Engineering, Inha University,
    Incheon 402-751, Republic of Korea
    3. Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and
    Telecommunications, Chongqing 400065, China
  • Received:2011-02-28 Revised:2011-06-02 Online:2012-05-30 Published:2012-05-30

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Abstract:

A virtual reconfigurable architecture-based intrinsic evolvable hardware (EHW) is proposed for the molecular classification of cancer. To efficiently process DNA microarray datasets and cooperate with the hardware realization of EHW, five different filter-based gene selection methods are compared and discussed in this paper. The EHW classification system handles the selected informative genes through two stages: system
learning and system classification. Empirical studies on a human acute leukemia dataset demonstrate that classification accuracy of the gene selection scheme based on signal-to-noise ratio outperforms its competitors. Classification accuracy of the proposed EHW is high comparable with other state-of-the-art pattern recognition methods. The system recognition time is reduced to 0.12 ms.

Key words: pattern recognition, evolvable hardware, feature selection, virtual reconfigurable architecture, microarray, molecular classification

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