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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2004: Applications of Evolutionary Computing pp 11–20Cite as

An Improved Genetic Algorithm for the Sequencing by Hybridization Problem

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3005))

Abstract

This paper presents a genetic algorithm for a computational biology problem. The problem appears in the computational part of a new deoxyribonucleic acid (DNA) sequencing procedure denominated sequencing by hybridization (SBH). The proposed genetic algorithm is an improvement over a recently proposed algorithm in the literature. The improvement is achieved by modifying the crossover operator towards an almost deterministic greedy crossover which makes the algorithm both more effective and more efficient. Experimental results on real DNA data are presented to show the advantages of using the proposed algorithm.

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Author information

Authors and Affiliations

  1. Computer Science Department, CICESE Research Center Km 107 Carr. Tijuana-Ensenada, Ensenada, B.C., México

    Carlos A. Brizuela, Luis C. González & Heidi J. Romero

Authors
  1. Carlos A. Brizuela
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  2. Luis C. González
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  3. Heidi J. Romero
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Editor information

Editors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9–11/1861, 1040, Vienna, Austria

    Günther R. Raidl

  2. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  3. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  4. School of Mathematical and Computer Science, Heriot-Watt University, EH14 8AS, Edinburgh, UK

    David Wolfe Corne

  5. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  6. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

  7. Computing Laboratory, University of Kent, Canterbury, UK

    Colin G. Johnson

  8. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  9. ICIS, Radboud University Nijmegen, The Netherlands

    Elena Marchiori

  10. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  11. School of Computing Sciences, UEA Norwich, University of East Anglia, NR4 7TJ, Norwich, UK

    George D. Smith

  12. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Brizuela, C.A., González, L.C., Romero, H.J. (2004). An Improved Genetic Algorithm for the Sequencing by Hybridization Problem. In: Raidl, G.R., et al. Applications of Evolutionary Computing. EvoWorkshops 2004. Lecture Notes in Computer Science, vol 3005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24653-4_2

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  • DOI: https://doi.org/10.1007/978-3-540-24653-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21378-9

  • Online ISBN: 978-3-540-24653-4

  • eBook Packages: Springer Book Archive

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