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Promoter Prediction with a GP-Automaton

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Applications of Evolutionary Computing (EvoWorkshops 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2611))

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Abstract

A GP-automaton evolves motif sequences for its states; it moves the point of motif application at transition time using an integer that is stored and evolved in the transition; and it combines motif matches via logical functions that it also stores and evolves in each transition. This scheme learns to predict promoters in human genome. The experiments reported use 5-fold cross validation.

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References

  1. Ashlock, D. (1997). GP-Automata for dividing the dollar. In Koza et. al. (Eds) Genetic Programming: Proceedings of the Second Annual Conference, 18–26, Stanford University.

    Google Scholar 

  2. Benson, K. A. (2000). Evolving Finite State Machines with Embedded Genetic Programming for Automatic Target Detection within SAR Imagery In Proceedings of the Congress on Evolutionary Computation, 1543–1549, La Jolla, San Diego, USA.

    Google Scholar 

  3. Benson, K. A. (2000). Performing Automatic Target Detection with evolvable finite state automata. In Journal of Image and Vision Computing, Volume 20, Issue 9–10, Elsevier.

    Google Scholar 

  4. Cattaneo E., Rigamonti D., Zuccato C. The Enigma of Huntington’s Disease. Scientific American, December 2002.

    Google Scholar 

  5. Hannenhalli S. and Levy S. (2001). Promoter prediction in the human genome. In Proceedings of the 9th International Conference on Intelligent Systems for Molecular Biology. Copenhagen, Denmark, July 21-25, 2001, Bioinformatics, Vol 17, Supplement 1, pp. S90–S96. ISSN: 1367-4803.

    Google Scholar 

  6. John R. Koza (1999). Genetic Programming III: Darwinian Invention and Problem Solving, MIT Press.

    Google Scholar 

  7. Benjamin Lewin (2000). Genes VII, Oxford University Press.

    Google Scholar 

  8. Orphanides, G., Lagrange, T., Reinberg, D.. The general transcription factors of RNA polymerase II. Genes. Dev., vol. 10, 2657–2683, 1996.

    Article  Google Scholar 

  9. Pedersen, A. G., Baldi, P., Chauvin, Y., Brunak, S. The biology of eukaryotic promoter prediction-a review. Computers and Chemistry, vol. 23, 191–207, 1999.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Software Evolution Centre, Knowledge and Information Systems Division, QinetiQ Ltd, Malvern Technology Centre, St Andrews Road, WORCS WR14 3PS, Malvern, 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. Dept. of Computer Engineering, University of Parma, Parco Area delle Scienze 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  2. Computing Laboratory, University of Kent, Canterbury, Kent, CT2 7NF, UK

    Colin G. Johnson

  3. Dept. of Information and Communications Technologies Faculty of Computer Science, University of A Coruña, A Coruña, CP 15071, Spain

    Juan J. Romero Cardalda

  4. Dept. of Mathematics and Computer Science, Free University of Amsterdam, de Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands

    Elena Marchiori

  5. Schol of Systems Engineering, University of Reading, PO Box 225, Whiteknights, Reading, RG6 6AY, UK

    David W. Corne

  6. AnimatLab, 8 rue du capitaine Scott, 75015, Paris, France

    Jean-Arcady Meyer  & Agnès Guillot  & 

  7. SAP AG, Neurottstrasse 16, 69190, Walldorf, Germany

    Jens Gottlieb

  8. Parallel Computing and Complex Systems Group, University of Leipzig, Augustusplatz 10/11, 04109, Leipzig, Germany

    Martin Middendorf

  9. Algorithms and Data Structures Group Institute of Computer Graphics, Vienna University of Technology, Favoritenstrasse 9-11/186, 1040, Vienna, Austria

    Günther R. Raidl

  10. School of Computing, Napier University, 219 Colinton Road, Edinburgh, EH14 1DJ, UK

    Emma Hart

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© 2003 Springer-Verlag Berlin Heidelberg

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Howard, D., Benson, K. (2003). Promoter Prediction with a GP-Automaton. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_5

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  • DOI: https://doi.org/10.1007/3-540-36605-9_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00976-4

  • Online ISBN: 978-3-540-36605-8

  • eBook Packages: Springer Book Archive

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