25. Survey on Biclustering of Gene Expression Data

  1. Mourad Elloumi6 and
  2. Albert Y. Zomaya7
  1. Adelaide Valente Freitas1,
  2. Wassim Ayadi2,3,
  3. Mourad Elloumi2,4,
  4. Joséluis Oliveira5,
  5. Joséluis Oliveira5 and
  6. Jin-Kao Hao3

Published Online: 27 DEC 2013

DOI: 10.1002/9781118617151.ch25

Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data

Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data

How to Cite

Freitas, A. V., Ayadi, W., Elloumi, M., Oliveira, J., Oliveira, J. and Hao, J.-K. (2013) Survey on Biclustering of Gene Expression Data, in Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data (eds M. Elloumi and A. Y. Zomaya), John Wiley & Sons, Inc., Hoboken, New Jersey. doi: 10.1002/9781118617151.ch25

Editor Information

  1. 6

    Laboratory of Technologies of Information and Communication and Electrical, Engineering (LaTICE) and University of Tunis-El Manar, Tunisia

  2. 7

    The University of Sydney

Author Information

  1. 1

    DMat/CIDMA, University of Aveiro, Portugal

  2. 2

    Laboratory of Technologies of Information and Communication and Electrical Engineering (LaTICE)

  3. 3

    LERIA, University of Angers, Angers, France

  4. 4

    University of Tunis-El Manar, Tunisia

  5. 5

    DETI/IEETA, University of Aveiro, Portugal

Publication History

  1. Published Online: 27 DEC 2013
  2. Published Print: 16 DEC 2013

ISBN Information

Print ISBN: 9781118132739

Online ISBN: 9781118617151

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Keywords:

  • bicluster validation;
  • biclusters;
  • evaluation functions;
  • gene expression data;
  • stochastic biclustering algorithms

Summary

Microarrays allow measuring the expression level of a large number of genes under different experimental samples or environmental conditions. The data generated from them are called gene expression data. Gene expression data are usually represented by a matrix M, where the ith row represents the ith gene, the jth column represents the jth condition, and the cell mij represents the expression level of the th gene under the jth condition. In this chapter, the authors make a survey on biclustering of gene expression data. First, the chapter presents the different types of biclusters and groups of biclusters. Then, it discusses the evaluation functions and systematic and stochastic biclustering algorithms. Finally, the chapter focuses on bicluster validation that can qualitatively evaluate the capacity of an algorithm to extract meaningful biclusters from a biological point of view.