Abstract
This paper proposes an analytic framework for the analysis of evolutionary mechanisms at genetic coding level, attempting to provide more detailed description than population genetics. It gives an estimated sequence after T replications in an environment given the initial genetic sequence. We assume that there is a principle obeyed by evolutionary mechanisms at genetic sequence level, such that some law, called action, is suboptimal. We propose such an action for haploid, asexual type living lives with replications involving only point mutations, as a function of fitness and the probability of change in sequence, so the evolutionary process is not a simple hill-climbing. Our method provides an intuitive view on evolution of genetic sequences, and it may be a powerful analysis tool when we need to treat directly the genetic sequence. It is useful for the analysis of real or artificial life such as genetic algorithms. This is a report of a work in progress, and we present the background, development, connection with population genetics, and some possible extensions of our work.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Crow, J. F.: Basic Concepts in Population, Quantitative, and Evolutionary Genetics. W. H. Freeman and Co. (1986)
Crow, J. F. and Kimura, M.: An Introduction to Population Genetics Thory. Harper & Row (1970)
Feynman, R. P., and Hibbs, A. R.: Quantum Mechanics and Path Integrals. McGraw-Hill (1965)
Gillespie, J. H: The Causes of Molecular Evolution, Oxford Univ. Press (1991)
Kauffman, S. A.: The Origins of Order, Oxford Univ. Press (1993)
Kimura, M.: Optimum mutation rate and degree of dominance as determined by the principle of minimum genetic load. Journal of Genetics 57 (1960)
Kimura, M.: On. the evolutionary adjustment of spontaneous mutation rates. Genet. Res. 9 (1967)
Kimura, M.: The Neutral Theory of Molecular Evolution, Cambridge Univ. Press (1983)
Macken, C. A. and Perelson, A. S: Protein evolution on rugged landscapes. Proc. Natl. Acad. Sci. USA. 86 (1989)
Muller, H. J.: Our load of mutations. American Journal of Human Genetics. 2 (1950)
Nei, M.: Molecular Evolutionary Genetics, Columbis Univ. Press (1987)
Nishikawa, K., Ishino, S., Takenaka, H., Norioka, N., Hirai, T., Yao, T. and Seto, Y.: Constructing a protein mutant database. Protein Engineering. 7 (1993)
Perelson, A. S. and Kauffman, S. A.: Molecular Evolution on Rugged Landscapes: Proteins, RNA and the Immune System. Addison-Wesley (1989)
Reidhaar-Olson, G. F. and Sauer, R. T.: Combinatorial cassette mutagenesis as a probe of the informational content of protein sequences. Science. 241 (1988)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maeshiro, T., Kimura, M. (1995). Mathematical analysis of evolutionary process. In: Morán, F., Moreno, A., Merelo, J.J., Chacón, P. (eds) Advances in Artificial Life. ECAL 1995. Lecture Notes in Computer Science, vol 929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59496-5_306
Download citation
DOI: https://doi.org/10.1007/3-540-59496-5_306
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-59496-3
Online ISBN: 978-3-540-49286-3
eBook Packages: Springer Book Archive