Mutation (genetic algorithm)

About: Mutation (genetic algorithm) is a research topic. Over the lifetime, 31223 publications have been published within this topic receiving 720553 citations.

Mutation of the mouse klotho gene leads to a syndrome resembling ageing

Abstract: A new gene, termed klotho, has been identified that is involved in the suppression of several ageing phenotypes. A defect in klotho gene expression in the mouse results in a syndrome that resembles human ageing, including a short lifespan, infertility, arteriosclerosis, skin atrophy, osteoporosis and emphysema. The gene encodes a membrane protein that shares sequence similarity with the β-glucosidase enzymes. The klotho gene product may function as part of a signalling pathway that regulates ageing in vivo and morbidity in age-related diseases.

The Number of Alleles That Can Be Maintained in a Finite Population

Abstract: T has sometimes been suggested that the wild-type allele is not a single entity, I but rather a population of different isoalleles that are indistinguishable by any ordinary procedure. With hundreds of nucleotides, each presumably capable of base substitutions and with additional permutations possible through sequence rearrangements, gains, and losses, the number of possible gene states becomes astronomical. It is known that a single nucleotide substitution can have the most drastic consequences, but there are also mutations with very minute effects and there is the possibility that many are so small as to be undetectable. It is not the purpose of this article to discuss the plausibility of such a system of isoalleles, or the evidence for and against. Instead, we propose to examine some of the population consequences of such a system if it does exist. The probability seems great enough to warrant such an inquiry. If a large number of different states can arise by mutation, this doesn't necessarily mean that a large fraction of these would coexist in a single population. Some will be lost by random drift and others may be selectively disadvantageous. On the other hand, some may persist by being beneficial in heterozygous combinations. We shall consider three possibilities: ( 1 ) A system of selectively neutral isoalleles whose frequency in the population is determined by the mutation rate and by random drift. (2) A system of mutually heterotic alleles. ( 3 ) A mixture of heterotic and harmful mutants.

Adaptive probabilities of crossover and mutation in genetic algorithms

Abstract: In this paper we describe an efficient approach for multimodal function optimization using genetic algorithms (GAs). We recommend the use of adaptive probabilities of crossover and mutation to realize the twin goals of maintaining diversity in the population and sustaining the, convergence capacity of the GA. In the adaptive genetic algorithm (AGA), the probabilities of crossover and mutation, p/sub c/ and p/sub m/, are varied depending on the fitness values of the solutions. High-fitness solutions are 'protected', while solutions with subaverage fitnesses are totally disrupted. By using adaptively varying p/sub c/ and p/sub ,/ we also provide a solution to the problem of deciding the optimal values of p/sub c/ and p/sub m/, i.e., p/sub c/ and p/sub m/ need not be specified at all. The AGA is compared with previous approaches for adapting operator probabilities in genetic algorithms. The Schema theorem is derived for the AGA, and the working of the AGA is analyzed. We compare the performance of the AGA with that of the standard GA (SGA) in optimizing several nontrivial multimodal functions with varying degrees of complexity. >

The genetic landscape of a cell.

Abstract: A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.