13. Gene Microarray Data Analysis Using Parallel Point Symmetry-Based Clustering

  1. Ujjwal Maulik2,
  2. Sanghamitra Bandyopadhyay3 and
  3. Jason T. L. Wang4
  1. Ujjwal Maulik2 and
  2. Anasua Sarkar1

Published Online: 25 AUG 2010

DOI: 10.1002/9780470872352.ch13

Computational Intelligence and Pattern Analysis in Biological Informatics

Computational Intelligence and Pattern Analysis in Biological Informatics

How to Cite

Maulik, U. and Sarkar, A. (2010) Gene Microarray Data Analysis Using Parallel Point Symmetry-Based Clustering, 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.ch13

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

    LaBRI, University Bordeaux 1, France

  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

SEARCH

Keywords:

  • gene microarray data analysis - using parallel point symmetry-based clustering;
  • performance analysis - algorithms PKM, ParSBKM and ParPSBKM using MPI (message passing interface) and C;
  • ParSBKM performance with data sizes - and increasing number of processors

Summary

This chapter contains sections titled:

  • Introduction

  • Symmetry- and Point Symmetry-Based Distance Measures

  • Parpsbkm Clustering Implementation

  • Performance Analysis

  • Test for Statistical Significance

  • Conclusions

  • References