9. Integer Linear Programming Techniques for Discovering Approximate Gene Clusters

  1. Ion I. Mǎndoiu4 and
  2. Alexander Zelikovsky5
  1. Sven Rahmann1 and
  2. Gunnar W. Klau2,3

Published Online: 9 AUG 2007

DOI: 10.1002/9780470253441.ch9

Bioinformatics Algorithms: Techniques and Applications

Bioinformatics Algorithms: Techniques and Applications

How to Cite

Rahmann, S. and Klau, G. W. (2008) Integer Linear Programming Techniques for Discovering Approximate Gene Clusters, in Bioinformatics Algorithms: Techniques and Applications (eds I. I. Mǎndoiu and A. Zelikovsky), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470253441.ch9

Editor Information

  1. 4

    Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA

  2. 5

    Department of Computer Science, Georgia State University, Atlanta, GA, USA

Author Information

  1. 1

    Bioinformatics for High-Throughput Technologies, Department of Computer Science 11, Technical University of Dortmund, Dortmund, Germany

  2. 2

    Mathematics in Life Sciences Group, Department of Mathematics and Computer Science, University Berlin, Germany

  3. 3

    DFG Research Center Matheon “Mathematics for Key Technologies”, Berlin, Germany

Publication History

  1. Published Online: 9 AUG 2007
  2. Published Print: 8 FEB 2008

ISBN Information

Print ISBN: 9780470097731

Online ISBN: 9780470253441

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Keywords:

  • integer linear programs (ILPs);
  • approximate gene cluster discovery problem (AGCDP);
  • error-tolerant formalization

Summary

This chapter contains sections titled:

  • Introduction

  • Basic Problem Specification

  • Integer Linear Programming Formulation

  • Extensions and Variations

  • Computational Results

  • Discussion

  • Acknowledgments

  • References