Genetic code optimality studied by means of simulated evolution and within the coevolution theory of the canonical code organization
We have studied the canonical genetic code optimality by means of simulated evolution. A genetic algorithm is used to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes. Such analysis is performed within the coevolution theory of the genetic code organization. We have studied the progression of the canonical genetic code optimality within such theory, considering a possible scenario of a previous code with two-letter codons as well as the current organization of the canonical code. Moreover, we have analysed the particular optimality and progression of adaptability of the individual nucleotide bases.
genetic algorithms coevolution theory of the genetic code genetic code theories error-minimization hypothesis