Abstract
In this work we use simulated evolution to corroborate the adaptability of the natural genetic code. An adapted genetic algorithm searches for optimal hypothetical codes. The adaptability is measured as the average variation of the hydrophobicity that experiment the encoded amino acids when errors or mutations are presented in the codons of the hypothetical codes. Different types of mutations and base position mutation probabilities are considered in this study. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Monteagudo, Á., & Santos, J. (2007). Simulated evolution of the adaptability of the genetic code using genetic algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4527 LNCS, pp. 478–487). Springer Verlag. https://doi.org/10.1007/978-3-540-73053-8_48
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
