Measuring rate of evolution in genetic programming using amino acid to synonymous substitution ratio ka/ks

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Measuring rate of evolution in genetic programming using amino acid to synonymous substitution ratio k_a/k_s

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents

Atlanta, GA, USA

SESSION: Genetic Programming Postes table of contents

Pages 1337-1338

Year of Publication: 2008

ISBN:978-1-60558-130-9

Authors

Ting Hu	Memorial University of Newfoundland, St. John's, NF, Canada
Wolfgang Banzhaf	Memorial University of Newfoundland, St. John's, NF, Canada

Sponsors

ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

Publisher

ACM New York, NY, USA

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ABSTRACT

We define the rate of evolution R_e in a GP system based on the rate of efficient genetic variations being accepted. This definition is motivated by the measurement of "amino acid to synonymous substitution ratio" k_a/k_s in biology. Experimental applications of this rate of evolution measurement show that R_e well reflects how evolution proceeds underneath fitness development and quantifies the rate of innovation through efficient genetic variations.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	W. Banzhaf, G. Beslon, S. Christensen, J. A. Foster, F. Kepes, V. Lefort, J. F. Miller, M. Radman, and J. J. Ramsden. From artificial evolution to computational evolution: A research agenda. Nature Reviews Genetics, 7(9):729--735, September 2006.
	2	Z. Yang and J. P. Bielawski. Statistical methods for detecting molecular adaptation. Trends in Ecology and Evolution, 15(12):496--503, December 2000.