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Evolutionary Computation Method for Promoter Site Prediction in DNA

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2724))

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Abstract

This paper develops an evolutionary method that learns inductively to recognize the makeup and the position of very short consensus sequences, which are a typical feature of promoters in eukaryotic genomes. This class of method can be used to discover candidate promoter sequences in primary sequence data. If further developed, it has the potential to discover genes which are regulated together.

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Author information

Authors and Affiliations

  1. Software Evolution Centre, Knowledge and Information Systems, QinetiQ, St Andrews Road, Malvern, Worcs, WR14 3PS, UK

    Daniel Howard & Karl Benson

Authors
  1. Daniel Howard
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  2. Karl Benson
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Editor information

Editors and Affiliations

  1. Center for Applied Scientific Computing (CASC), Lawrence Livermore National Laboratory, 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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© 2003 Springer-Verlag Berlin Heidelberg

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Howard, D., Benson, K. (2003). Evolutionary Computation Method for Promoter Site Prediction in DNA. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_62

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  • DOI: https://doi.org/10.1007/3-540-45110-2_62

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40603-7

  • Online ISBN: 978-3-540-45110-5

  • eBook Packages: Springer Book Archive

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