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Setting aside other factors (e.g., balancing selection, and genetic drift), the equilibrium number of deleterious alleles is then determined by a balance between the deleterious mutation rate and the rate at which selection purges those mutations. Mutation–selection balance was originally proposed to explain how genetic variation is ...
Selection coefficient, usually denoted by the letter s, is a measure used in population genetics to quantify the relative fitness of a genotype compared to other genotypes. . Selection coefficients are central to the quantitative description of evolution, since fitness differences determine the change in genotype frequencies attributable to selecti
An additional concern is that the effects of time must be incorporated into an analysis, if the lineages being compared are closely related; this is because it can take a number of generations for natural selection to "weed out" deleterious mutations from a population, especially if their effect on fitness is weak.
The Haldane-Muller theorem of mutation–selection balance says that the load depends only on the deleterious mutation rate and not on the selection coefficient. [6] Specifically, relative to an ideal genotype of fitness 1, the mean population fitness is exp ( − U ) {\displaystyle \exp(-U)} where U is the total deleterious mutation rate ...
Balancing selection refers to a number of selective processes by which multiple alleles (different versions of a gene) are actively maintained in the gene pool of a population at frequencies larger than expected from genetic drift alone. Balancing selection is rare compared to purifying selection. [1]
The adaptive value can be measured by contribution of an individual to the gene pool of their offspring. The adaptive values are approximately calculated from the rates of change in frequency and mutation–selection balance. [2]
If the selection and crossover operators are used without the mutation operator, the algorithm will tend to converge to a local minimum, that is, a good but sub-optimal solution to the problem. Using the mutation operator on its own leads to a random walk through the search space. Only by using all three operators together can the evolutionary ...
Evolutionary programming – Similar to evolution strategy, but with a deterministic selection of all parents. Evolution strategy (ES) – Works with vectors of real numbers as representations of solutions, and typically uses self-adaptive mutation rates. The method is mainly used for numerical optimization, although there are also variants for ...
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