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A Novel Method for Gene Selection and Cancer Classification

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Book cover Advances in Neural Networks - ISNN 2004 (ISNN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3174))

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Abstract

Accurate diagnosis among a group of histologically similar cancers is a challenging issue in clinical medicine. Microarray technology brings new inspiration in solving this problem on genes level. In this paper, a novel gene selection method is proposed and a BP classifier is constructed for gene expression-based cancer classification. By testing on the open leukemia data set, it shows excellent classification performance. 100% classification accuracy is achieved when 46 informative genes are selected. Reducing genes number to 6, only a sample is misclassified. This study provides a reliable method for molecular cancer classification, and may offer insights into biological and clinical researches.

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References

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Author information

Authors and Affiliations

  1. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, People’s Republic of China

    Huajun Yan & Zhang Yi

Authors
  1. Huajun Yan
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  2. Zhang Yi
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Editor information

Editors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, China

    Fu-Liang Yin

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, Liaoning, China

    Chengan Guo

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© 2004 Springer-Verlag Berlin Heidelberg

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Yan, H., Yi, Z. (2004). A Novel Method for Gene Selection and Cancer Classification. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_74

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  • DOI: https://doi.org/10.1007/978-3-540-28648-6_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22843-1

  • Online ISBN: 978-3-540-28648-6

  • eBook Packages: Springer Book Archive

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