Figure 1.

Evolutionary computing methodology applied to the search for better adapted codes. (a) Each individual of a genetic population encodes a possible hypothetical code, which is evaluated according to its efficiency to changes or mutations in the codon bases. (b) This efficiency defines the fitness of each individual, which is used by the genetic algorithm to select the individuals (c) in which a genetic operator (swap) is applied to define the individuals of the next generation (model 1 of hypothetical codes). (d) This evolutionary process is iterated through generations.