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Clustering Protein Interaction Data Through Chaotic Genetic Algorithm

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Simulated Evolution and Learning (SEAL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4247))

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Abstract

In this paper, we proposed a Chaotic Genetic Algorithm (CGA) to cluster protein interaction data to find protein complexes. Compared with other computation methods, the main advantage of this method is that it can find as many potential protein complexes as possible. Application on the Yeast genomic data highlights the efficiency of our method.

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Author information

Authors and Affiliations

  1. School of Computer, Wuhan University, Wuhan, 430079, China

    Hongbiao Liu & Juan Liu

Authors
  1. Hongbiao Liu
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  2. Juan Liu
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Editor information

Editors and Affiliations

  1. Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung County Taiwan, ROC

    Tzai-Der Wang

  2. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  3. AI-ECON Research Center, Department of Economics, National Chengchi University, 11623, Taipei, Taiwan

    Shu-Heng Chen

  4. Department of Computer Science and Technology, University of Sci. & Tech. of China, 230026, Hefei, Anhui, P.R. China

    Xufa Wang

  5. School of Information Technology and Electrical Engineering, University of New South Wales, Australian Defence Force Academy, Canberra, Australia

    Hussein Abbass

  6. The Univertity of Tokyo, Japan

    Hitoshi Iba

  7. Department of Computer, University of Science and Technology of China, 230027, Hefei, China

    Guo-Liang Chen

  8. University of Birmingham, Birmingham, UK

    Xin Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Liu, H., Liu, J. (2006). Clustering Protein Interaction Data Through Chaotic Genetic Algorithm. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_108

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  • DOI: https://doi.org/10.1007/11903697_108

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47331-2

  • Online ISBN: 978-3-540-47332-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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