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Genetic and Evolutionary Computation Conference

GECCO 2004: Genetic and Evolutionary Computation – GECCO 2004 pp 908–919Cite as

An Enhanced Genetic Algorithm for DNA Sequencing by Hybridization with Positive and Negative Errors

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3103))

Abstract

This paper describes a genetic algorithm for the DNA sequencing problem. The algorithm allows the input spectrum to contain both positive and negative errors as could be expected from a hybridization experiment. The main features of the algorithm include a preprocessing step that reduces the size of the input spectrum and an efficient local optimization. In experimental tests, the algorithm performed very well against existing algorithms. The algorithm also performed very well on a large data set generated in this paper from real genomes data.

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Author information

Authors and Affiliations

  1. Department of Computer Science, The Pennsylvania State University at Harrisburg, Middletown, PA, 17057, USA

    Thang N. Bui & Waleed A. Youssef

Authors
  1. Thang N. Bui
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  2. Waleed A. Youssef
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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© 2004 Springer-Verlag Berlin Heidelberg

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Bui, T.N., Youssef, W.A. (2004). An Enhanced Genetic Algorithm for DNA Sequencing by Hybridization with Positive and Negative Errors. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_104

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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