11. Integrated Differential Fuzzy Clustering for Analysis of Microarray Data

  1. Ujjwal Maulik2,
  2. Sanghamitra Bandyopadhyay3 and
  3. Jason T. L. Wang4
  1. Indrajit Saha1 and
  2. Ujjwal Maulik2

Published Online: 25 AUG 2010

DOI: 10.1002/9780470872352.ch11

Computational Intelligence and Pattern Analysis in Biological Informatics

Computational Intelligence and Pattern Analysis in Biological Informatics

How to Cite

Saha, I. and Maulik, U. (2010) Integrated Differential Fuzzy Clustering for Analysis of Microarray Data, in Computational Intelligence and Pattern Analysis in Biological Informatics (eds U. Maulik, S. Bandyopadhyay and J. T. L. Wang), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470872352.ch11

Editor Information

  1. 2

    Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

  2. 3

    Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

  3. 4

    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA

Author Information

  1. 1

    Interdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Poland

  2. 2

    Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

Publication History

  1. Published Online: 25 AUG 2010
  2. Published Print: 11 OCT 2010

ISBN Information

Print ISBN: 9780470581599

Online ISBN: 9780470872352

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Keywords:

  • microarray data analysis - integrated differential fuzzy clustering for microarray data analysis;
  • clustering algorithms and validity measure;
  • integrated fuzzy clustering with support vector machines (SVMs)

Summary

This chapter contains sections titled:

  • Introduction

  • Clustering Algorithms and Validity Measure

  • Differential Evolution Based Fuzzy Clustering

  • Experimental Results

  • Integrated Fuzzy Clustering with Support Vector Machines

  • Conclusion

  • References