Effects of Selection and Drift on the Dynamics of Finite Populations II. Expected Time to Fixation or Loss of an Allele

Biometrics ◽  
1970 ◽  
Vol 26 (2) ◽  
pp. 221 ◽  
Author(s):  
R. N. Carr ◽  
R. F. Nassar
Keyword(s):  
Finite Populations ◽  
Expected Time

Measuring Expected Time to Default Under Stress Conditions for Corporate Loans

2016 ◽  
Author(s):  
Mariusz GGrajski ◽  
Zuzanna Wooko
Keyword(s):  
Stress Conditions ◽  
Expected Time

Adaptive routing using the expected time in tandem queues.

1984 ◽  
Author(s):  
Ivan Taylor
Keyword(s):  
Adaptive Routing ◽  
Tandem Queues ◽  
Expected Time

scholarly journals Asymptotic Expansions and Strategies in the Online Increasing Subsequence Problem

2021 ◽  
Vol 174 (1) ◽  
Author(s):  
Amirlan Seksenbayev
Keyword(s):  
Dynamic Programming ◽  
Asymptotic Expansions ◽  
Dual Problem ◽  
Infinite Length ◽  
Expected Time ◽  
Selection Strategies ◽  
Dynamic Programming Equation ◽  
Optimal Values ◽  
Design Selection ◽  
Selection Of

AbstractWe study two closely related problems in the online selection of increasing subsequence. In the first problem, introduced by Samuels and Steele (Ann. Probab. 9(6):937–947, 1981), the objective is to maximise the length of a subsequence selected by a nonanticipating strategy from a random sample of given size $n$ n . In the dual problem, recently studied by Arlotto et al. (Random Struct. Algorithms 49:235–252, 2016), the objective is to minimise the expected time needed to choose an increasing subsequence of given length $k$ k from a sequence of infinite length. Developing a method based on the monotonicity of the dynamic programming equation, we derive the two-term asymptotic expansions for the optimal values, with $O(1)$ O ( 1 ) remainder in the first problem and $O(k)$ O ( k ) in the second. Settling a conjecture in Arlotto et al. (Random Struct. Algorithms 52:41–53, 2018), we also design selection strategies to achieve optimality within these bounds, that are, in a sense, best possible.

scholarly journals Recombination Can Evolve in Large Finite Populations Given Selection on Sufficient Loci

Genetics ◽  
2003 ◽  
Vol 165 (4) ◽  
pp. 2249-2258 ◽  
Author(s):  
Mark M Iles ◽  
Kevin Walters ◽  
Chris Cannings
Keyword(s):  
Experimental Evidence ◽  
Genetic Drift ◽  
Finite Population ◽  
Selective Advantage ◽  
Indirect Selection ◽  
Small Populations ◽  
Finite Populations ◽  
Population Sizes ◽  
Population Recombination

AbstractIt is well known that an allele causing increased recombination is expected to proliferate as a result of genetic drift in a finite population undergoing selection, without requiring other mechanisms. This is supported by recent simulations apparently demonstrating that, in small populations, drift is more important than epistasis in increasing recombination, with this effect disappearing in larger finite populations. However, recent experimental evidence finds a greater advantage for recombination in larger populations. These results are reconciled by demonstrating through simulation without epistasis that for m loci recombination has an appreciable selective advantage over a range of population sizes (am, bm). bm increases steadily with m while am remains fairly static. Thus, however large the finite population, if selection acts on sufficiently many loci, an allele that increases recombination is selected for. We show that as selection acts on our finite population, recombination increases the variance in expected log fitness, causing indirect selection on a recombination-modifying locus. This effect is enhanced in those populations with more loci because the variance in phenotypic fitnesses in relation to the possible range will be smaller. Thus fixation of a particular haplotype is less likely to occur, increasing the advantage of recombination.

scholarly journals The Rate of Compensatory Evolution

Genetics ◽  
1996 ◽  
Vol 144 (1) ◽  
pp. 419-426 ◽  
Author(s):  
Wolfgang Stephan
Keyword(s):  
Diffusion Theory ◽  
Secondary Structures ◽  
Compensatory Mutation ◽  
Weak Selection ◽  
Mutation Pressure ◽  
Theory Of Evolution ◽  
Compensatory Evolution ◽  
Expected Time ◽  
Individual Fitness ◽  
Shifting Balance

Abstract A two-locus model is presented to analyze the evolution of compensatory mutations occurring in stems of RNA secondary structures. Single mutations are assumed to be deleterious but harmless (neutral) in appropriate combinations. In proceeding under mutation pressure, natural selection and genetic drift from one fitness peak to another one, a population must therefore pass through a valley of intermediate deleterious states of individual fitness. The expected time for this transition is calculated using diffusion theory. The rate of compensatory evolution, kc, is then defined as the inverse of the expected transition time. When selection against deleterious single mutations is strong, kc, depends on the recombination fraction r between the two loci. Recombination generally reduces the rate of compensatory evolution because it breaks up favorable combinations of double mutants. For complete linkage, kc, is given by the rate at which favorable combinations of double mutantS are produced by compensatory mutation. For r > 0, kc, decreases exponentially with r. In contrast, kc, becomes independent of r for weak selection. We discuss the dynamics of evolutionary substitutions of compensatory mutants in relation to Wright'S shifting balance theory of evolution and use our results to analyze the substitution process in helices of mRNA secondary structures.

Ovarian and endocrine responses to prostaglandin F2α (PGF2α) given at the expected time of the endogenous FSH peak at mid-cycle in ewes

2006 ◽  
Vol 66 (4) ◽  
pp. 811-821 ◽  
Author(s):  
Xinyu Liu ◽  
Qiao Dai ◽  
Ezra J. Hart ◽  
Rajesha Duggavathi ◽  
David M.W. Barrett ◽  
...  
Keyword(s):  
Prostaglandin F2α ◽  
Expected Time
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