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Utilising Neural Network and Support Vector Machine for Gene Expression Classification

Author

Listed:
  • Keivan Kianmehr

    (Department of Computer Science, University of Calgary Calgary, Alberta, Canada)

  • Hongchao Zhang

    (Department of Computer Science, University of Calgary Calgary, Alberta, Canada)

  • Konstantin Nikolov

    (Department of Computer Science, University of Calgary Calgary, Alberta, Canada)

  • Tansel Özyer

    (Department of Computer Science, University of Calgary Calgary, Alberta, Canada)

  • Reda Alhajj

    (Department of Computer Science, University of Calgary Calgary, Alberta, Canada)

Abstract

Bioinformatics is the science of managing, mining and interpreting information from biological sequences and structures. In this paper, we discuss two data-mining techniques that can be applied in bioinformatics: Neural Networks (NN) and Support Vector Machines (SVMs), and their application in gene expression classification. First, we provide a description of the two techniques. Then, we propose a new method that combines both SVM and NN. This way, we provide an effective knowledge management technique by utilising machine-learning techniques within the data-mining process. The knowledge obtained from the process is valuable as it is not possible to discover the same kind of knowledge using classical query processing or knowledge management techniques. Finally, we present the results obtained from our method and the results obtained from SVM alone on a sample data set.

Suggested Citation

  • Keivan Kianmehr & Hongchao Zhang & Konstantin Nikolov & Tansel Özyer & Reda Alhajj, 2007. "Utilising Neural Network and Support Vector Machine for Gene Expression Classification," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 251-260.
    • Handle: RePEc:wsi:jikmxx:v:06:y:2007:i:04:n:s0219649207001822
    DOI: 10.1142/S0219649207001822
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    Cited by:

    1. Madan Lal Yadav & Basav Roychoudhury, 2019. "Effectiveness of Domain-Based Lexicons vis-à-vis General Lexicon for Aspect-Level Sentiment Analysis: A Comparative Analysis," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-18, September.

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