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Gene Expression Data Classification Using Independent Variable Group Analysis

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

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Abstract

Microarrays are capable of detecting the expression levels of thousands of genes simultaneously. In this paper, a new method for gene selection based on independent variable group analysis is proposed. In this method, we first used t-statistics method to select a part of genes from the original data. Then we selected the key genes from the selected genes by t-statistics for tumor classification using IVGA. Finally, we used SVM to classify tumors based on the key genes selected using IVGA. To validate the efficiency, the proposed method is applied to classify three different DNA microarray data sets. The prediction results show that our method is efficient and feasible.

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Author information

Authors and Affiliations

  1. College of Information and Communication Technology, Qufu Normal University, Rizhao, Shandong, 276826, China

    Chunhou Zheng & Min Xu

  2. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, 230031, China

    Chunhou Zheng & Bo Li

  3. Biometric Research Center, Dept. of Computing, The Hong Kong Polytechnic University, Hong Kong, China

    Lei Zhang

Authors
  1. Chunhou Zheng
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  2. Lei Zhang
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  3. Bo Li
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  4. Min Xu
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Zheng, C., Zhang, L., Li, B., Xu, M. (2008). Gene Expression Data Classification Using Independent Variable Group Analysis. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_28

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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