Search results
Results from the WOW.Com Content Network
It is analogous to biological mutation. The classic example of a mutation operator of a binary coded genetic algorithm (GA) involves a probability that an arbitrary bit in a genetic sequence will be flipped from its original state. A common method of implementing the mutation operator involves generating a random variable for each bit in a ...
Nevertheless, the concept is still widely used in evolutionary genetics, e.g. to explain the persistence of deleterious alleles as in the case of spinal muscular atrophy, [5] [4] or, in theoretical models, mutation-selection balance can appear in a variety of ways and has even been applied to beneficial mutations (i.e. balance between selective ...
Loss-of-function mutations, also called inactivating mutations, result in the gene product having less or no function (being partially or wholly inactivated). When the allele has a complete loss of function ( null allele ), it is often called an amorph or amorphic mutation in Muller's morphs schema.
Somatic hypermutation (or SHM) is a cellular mechanism by which the immune system adapts to the new foreign elements that confront it (e.g. microbes).A major component of the process of affinity maturation, SHM diversifies B cell receptors used to recognize foreign elements and allows the immune system to adapt its response to new threats during the lifetime of an organism. [1]
Contemporary biologists accept that mutation and selection both play roles in evolution; the mainstream view is that while mutation supplies material for selection in the form of variation, all non-random outcomes are caused by natural selection. [59]
Random mutations are the ultimate source of genetic variation. Mutations are likely to be rare, and most mutations are neutral or deleterious, but in some instances, the new alleles can be favored by natural selection. Polyploidy is an example of chromosomal mutation. Polyploidy is a condition wherein organisms have three or more sets of ...
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 ...
Other mutation operators select a leaf (external node) of the tree and replace it with a randomly chosen leaf. Another mutation is to select at random a function (internal node) and replace it with another function with the same arity (number of inputs). Hoist mutation randomly chooses a subtree and replaces it with a subtree within itself.