Molecular Evolution in Time-Dependent Environments

  • Claus O. Wilke
  • Christopher Ronnewinkel
  • Thomas Martinetz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1674)

Abstract

The quasispecies theory is studied for dynamic replication landscapes. A meaningful asymptotic quasispecies is defined for periodic time dependencies. The quasispecies’ composition is constantly changing over the oscillation period. The error threshold moves towards the position of the time averaged landscape for high oscillation frequencies and follows the landscape closely for low oscillation frequencies.

Keywords

Error Threshold Master Sequence Similar Phase Diagram Quasispecies Theory Asymptotic Steady State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    M. Eigen, Naturwissenschaften 58, 465 (1971).CrossRefGoogle Scholar
  2. [2]
    M. Eigen and P. Schuster, The Hypercycle—A Principle of Natural Self-Organization (Springer-Verlag, Berlin, 1979).Google Scholar
  3. [3]
    M. Eigen, J. McCaskill, and P. Schuster, J. Phys. Chem. 92, 6881 (1988).CrossRefGoogle Scholar
  4. [4]
    M. Eigen, J. McCaskill, and P. Schuster, Adv. Chem. Phys. 75, 149 (1989).CrossRefGoogle Scholar
  5. [5]
    C. K. Biebricher, M. Eigen, and W. C. Gardiner, Jr., Biochemistry 22, 2544 (1983).CrossRefGoogle Scholar
  6. [6]
    B. L. Jones, Bull. Math. Biol. 41, 761 (1979).MATHMathSciNetGoogle Scholar
  7. [7]
    B. L. Jones, Bull. Math. Biol. 41, 849 (1979).MATHMathSciNetGoogle Scholar
  8. [8]
    L. Demetrius, P. Schuster, and K. Sigmund, Bull. Math. Biol. 47, 239 (1985).MATHMathSciNetGoogle Scholar
  9. [9]
    C. J. Thompson and J. L. McBride, Math. Biosci. 21, 127 (1974).MATHCrossRefMathSciNetGoogle Scholar
  10. [10]
    B. L. Jones, R. H. Enns, and S. S. Rangnekar, Bull. Math. Biol. 38, 15 (1976).MATHGoogle Scholar
  11. [11]
    O. Perron, Math. Ann. 64, 248 (1907).CrossRefMathSciNetGoogle Scholar
  12. [12]
    J. Swetina and P. Schuster, Biophys. Chem. 16, 329 (1982).CrossRefGoogle Scholar
  13. [13]
    A. Sasaki and Y. Iwasa, Genetics 115, 377 (1987).Google Scholar
  14. [14]
    K. Ishii, H. Matsuda, Y. Iwasa, and A. Sasaki, Genetics 121, 163 (1989).Google Scholar
  15. [15]
    T. Hirst, in Fourth European Conference on Artificial Life, edited by P. Husband and I. Harvey (MIT Press, Cambridge, MA, 1997), pp. 425–431.Google Scholar
  16. [16]
    A. J. Hirst and J. E. Rowe, J. theor. Biol. (1998), submitted.Google Scholar
  17. [17]
    C. O. Wilke, Evolutionary Dynamics in Time-Dependent Environments (Ph.D. thesis, Ruhr-Universität Bochum, 1999). http://www.neuroinformatik.ruhr-uni-bochum.de/ini/PEOPLE/wilke/ps/PhD.ps.gz.
  18. [18]
    C. Adami, Introduction to Artificial Life (Telos, Springer-Verlag Publishers, Santa Clara, 1998).MATHGoogle Scholar
  19. [19]
    M. Nilsson and N. Snoad, eprint physics/9904023 (1999).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Claus O. Wilke
    • 1
  • Christopher Ronnewinkel
    • 1
  • Thomas Martinetz
    • 1
  1. 1.Institut für NeuroinformatikRuhr-Universität BochumBochumGermany

Personalised recommendations