Skip to main content
Springer Nature Link
Log in

Evolving Turing Machines for Biosequence Recognition and Analysis

  • Conference paper
  • First Online:
Genetic Programming (EuroGP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2038))

Included in the following conference series:

  • 674 Accesses

Abstract

This article presents a genetic programming system for biosequence recognition and analysis. In our model, a population of Turing machines evolves the capability of biosequence recognition using genetic algorithms. We use HIV biosequences as the working example. Experimental results indicate that evolved Turing machines are capable of recognizing HIV biosequences in a collection of training sets. In addition, we demostrate that the evolved Turing machines can be used to approximate the multiple sequence alignment problem.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Aho, A.V., Hopcroft, J.E., Ullman, J.D. 1974. The Design and Analysis of Computer Algorithms. Third Edition. Addison Wesley Publishing Company.

    Google Scholar 

  2. Baase, S., Van Gelder, A. 2000. Computer Algorithms Introduction to Design and Analysis. Addison Wesley Publishing Company.

    Google Scholar 

  3. Baldi, P., Brunak, S. 1998. Bioinformatics The Machine Learning Approach. The MIT Press.

    Google Scholar 

  4. Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D. 1998. Genetic Programming An Introduction. Morgan Kaufmann Publishers, Inc..

    Google Scholar 

  5. Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley Publishing Company.

    Google Scholar 

  6. Hopcroft, J.E., Ullman, J.D. 1979. Introduction to Automata Theory, Languages and Computation Addison Wesley Publishing Company.

    Google Scholar 

  7. Hu, Y.J. 1998. Biopattern Discovery by Genetic Programming. In J. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D. Fogel, M. Garzon, D. Goldberg, H. Iba, R. Riolo (eds.) Genetic Programming 1998. Proceedings of the Third Annual Conference. pp 152–157, Morgan Kaufmann Publishers, Inc.

    Google Scholar 

  8. Koza, J.R., Bennett III, F.H., Andre, D., Keane, M.A. 1999. Genetic Programming III Darwinian Invention and Problem Solving Morgan Kaufmann Publishers, Inc.

    Google Scholar 

  9. Minsky, M. 1967. Computation: Finite and Infinite Machines Prentice Hall.

    Google Scholar 

  10. Mitchell, M. 1996. An Introduction to Genetic Algorithms The MIT Press.

    Google Scholar 

  11. Sipser, M. 1997. Introduction to the Theory of Computation. PWS Publishing Company.

    Google Scholar 

  12. Tanomaru, J. 1998. Evolving Turing Machines from Examples In J.-K. Hao, E. Lutton, E. Ronald, M. Schoenauer, D. Snyers (eds.) Artificial Evolution Third European Conference, AE’97 LNCS 1363. Springer-Verlag.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Módulo de Servicio Postal Campus Estado de México del ITESM, ITESM Campus Estado de México, 50, 52926, México, México

    Edgar E. Vallejo

  2. omputer Science Department, ITESM Campus Morelos, Ave. Paseo de la Reforma 182 Col. Lomas de Cuernavaca, 62589, Morelos, México

    Fernando Ramos

Authors
  1. Edgar E. Vallejo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fernando Ramos
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science, University of Birmingham, Birmingham

    Julian Miller

  2. Computer Science Institute, University of Lausanne, Lausanne

    Marco Tomassini

  3. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy

    Pier Luca Lanzi

  4. Computer Science and Information Systems, University of Limerick, Limerick

    Conor Ryan

  5. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Italy

    Andrea G. B. Tettamanzi

  6. Department of Computer Science, University College London, London

    William B. Langdon

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Vallejo, E.E., Ramos, F. (2001). Evolving Turing Machines for Biosequence Recognition and Analysis. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tettamanzi, A.G.B., Langdon, W.B. (eds) Genetic Programming. EuroGP 2001. Lecture Notes in Computer Science, vol 2038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45355-5_15

Download citation

  • DOI: https://doi.org/10.1007/3-540-45355-5_15

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41899-3

  • Online ISBN: 978-3-540-45355-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation