The Wild Side of Adaptive Mutation

Science ◽  
2003 ◽  
Vol 300 (5624) ◽  
pp. 1337f-1337
Keyword(s):  
Adaptive Mutation

scholarly journals Adaptive Mutation Requires No Mutagenesis—Only Growth Under Selection: A Response

Genetics ◽  
2003 ◽  
Vol 165 (4) ◽  
pp. 2319-2321
Author(s):  
John R Roth ◽  
Eric Kofoid ◽  
Frederick P Roth ◽  
Otto G Berg ◽  
Jon Seger ◽  
...  
Keyword(s):  
Adaptive Mutation

scholarly journals Furin and the adaptive mutation of SARS-COV2: a computational framework

2021 ◽  
Author(s):  
Ayesha Sohail ◽  
Sümeyye Tunc ◽  
Alessandro Nutini ◽  
Robia Arif
Keyword(s):  
Adaptive Mutation ◽  
Computational Framework

CMFuzz: context-aware adaptive mutation for fuzzers

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Xiajing Wang ◽  
Changzhen Hu ◽  
Rui Ma ◽  
Donghai Tian ◽  
Jinyuan He
Keyword(s):  
Adaptive Mutation ◽  
Context Aware

scholarly journals Large-Scale Adaptive Hitchhiking Upon High Recombination inDrosophila simulans

Genetics ◽  
2003 ◽  
Vol 165 (2) ◽  
pp. 895-900 ◽  
Author(s):  
Humberto Quesada ◽  
Ursula E M Ramírez ◽  
Julio Rozas ◽  
Montserrat Aguadé
Keyword(s):  
Genetic Linkage ◽  
Large Scale ◽  
Intermediate Frequency ◽  
Core Region ◽  
Adaptive Mutation ◽  
Nucleotide Variation ◽  
Extended Haplotype ◽  
Major Haplotype ◽  
Pattern Of Variation

AbstractNatural selection is expected to leave a characteristic footprint on neighboring nucleotide variation through the effects of genetic linkage. The size of the region affected is proportional to the strength of selection and greatly reduced with the recombinational distance from the selected site. Thus, the genomic footprint of selection is generally believed to be restricted to a small DNA stretch in normal and highly recombining regions. Here, we study the effect of selection on linked polymorphism (hitchhiking effect) by surveying nucleotide variation across a highly recombining ∼88-kb genomic fragment in an African population of Drosophila simulans. We find a core region of up to 38 kb with a major haplotype at intermediate frequency. The extended haplotype structure that gradually vanishes until disappearing is unusual for a highly recombining region. Both the presence in the structured genomic domain of a single major haplotype depleted of variability and the detected spatial pattern of variation along the ∼88-kb fragment are incompatible with neutral predictions in a panmictic population. A major role of demographic effects could also be discarded. The observed pattern of variation clearly provides evidence that directional selection has acted recently on this region, sweeping out variation around a strongly adaptive mutation. Our findings suggest a major role of positive selection in shaping DNA variability even in highly recombining regions.

scholarly journals Adaptive Mutation of a lacZ Amber Allele

Genetics ◽  
1998 ◽  
Vol 150 (3) ◽  
pp. 1329-1330
Author(s):  
Patricia L Foster ◽  
John Cairns
Keyword(s):  
Adaptive Mutation

scholarly journals Research on the inverse kinematics of manipulator using an improved self-adaptive mutation differential evolution algorithm

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110144
Author(s):  
Qianqian Zhang ◽  
Daqing Wang ◽  
Lifu Gao
Keyword(s):  
Differential Evolution ◽  
Objective Function ◽  
Inverse Kinematics ◽  
Differential Evolution Algorithm ◽  
Weight Coefficient ◽  
Adaptive Mutation ◽  
Feasible Region ◽  
Serial Manipulators ◽  
De Algorithm ◽  
Self Adaptive

To assess the inverse kinematics (IK) of multiple degree-of-freedom (DOF) serial manipulators, this article proposes a method for solving the IK of manipulators using an improved self-adaptive mutation differential evolution (DE) algorithm. First, based on the self-adaptive DE algorithm, a new adaptive mutation operator and adaptive scaling factor are proposed to change the control parameters and differential strategy of the DE algorithm. Then, an error-related weight coefficient of the objective function is proposed to balance the weight of the position error and orientation error in the objective function. Finally, the proposed method is verified by the benchmark function, the 6-DOF and 7-DOF serial manipulator model. Experimental results show that the improvement of the algorithm and improved objective function can significantly improve the accuracy of the IK. For the specified points and random points in the feasible region, the proportion of accuracy meeting the specified requirements is increased by 22.5% and 28.7%, respectively.

Non-revisiting genetic algorithm with adaptive mutation using constant memory

2016 ◽  
Vol 8 (3) ◽  
pp. 189-210 ◽  
Author(s):  
Yang Lou ◽  
Shiu Yin Yuen
Keyword(s):  
Genetic Algorithm ◽  
Adaptive Mutation

scholarly journals Evolution and evolvability: celebrating Darwin 200

2008 ◽  
Vol 5 (1) ◽  
pp. 44-46 ◽  
Author(s):  
John F.Y Brookfield
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Time Scales ◽  
Evolutionary Change ◽  
Adaptive Mutation ◽  
Genetic Covariances ◽  
The Relationship ◽  
The Way

The concept of ‘evolvability’ is increasingly coming to dominate considerations of evolutionary change. There are, however, a number of different interpretations that have been put on the idea of evolvability, differing in the time scales over which the concept is applied. For some, evolvability characterizes the potential for future adaptive mutation and evolution. Others use evolvability to capture the nature of genetic variation as it exists in populations, particularly in terms of the genetic covariances between traits. In the latter use of the term, the applicability of the idea of evolvability as a measure of population's capacity to respond to natural selection rests on one, but not the only, view of the way in which we should envisage the process of natural selection. Perhaps the most potentially confusing aspects of the concept of evolvability are seen in the relationship between evolvability and robustness.

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