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Combination of Network Construction and Cluster Analysis and Its Application to Traditional Chinese Medicine

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

Bayesian networks and cluster analysis are widely applied to network construction, data mining and causal discovery in bioinformation and medical researches. A Bayesian network is used to describe associations among a large number of variables, such as a gene network and a network describing relationships among symptoms. Cluster analysis is used to cluster associated variables, For example, genes with similar expressions or associated symptoms are grouped into a cluster. In this paper, we combine these approaches of network construction and cluster analysis together. On the one hand, we use Bayesian networks to explain relationships among variables in each cluster; on the other hand we use hierarchical cluster approach to assist network construction, and we propose a structure learning approach. In the stepwise approach, a subnetwork over a larger cluster is constructed by combining several subnetworks over small clusters whenever these small clusters are grouped together. The proposed approach is applied to a traditional Chinese medical study on a kidney disease.

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Author information

Authors and Affiliations

  1. School of Mathematical Sciences, Peking University, Beijing, 100871, China

    Mingfeng Wang, Zhi Geng & Feng Chen

  2. Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China

    Miqu Wang, Weijun Ding & Ming Liu

Authors
  1. Mingfeng Wang
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  2. Zhi Geng
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  3. Miqu Wang
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  4. Feng Chen
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  5. Weijun Ding
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  6. Ming Liu
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Editor information

Editors and Affiliations

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

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Wang, M., Geng, Z., Wang, M., Chen, F., Ding, W., Liu, M. (2006). Combination of Network Construction and Cluster Analysis and Its Application to Traditional Chinese Medicine. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_114

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  • DOI: https://doi.org/10.1007/11760191_114

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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