Sentence examples for constant selection for from inspiring English sources

By contrast, the 3DPCR error rate is of the order of 4 20 kb−1 owing to constant selection for AT DNA and PCR-mediated recombination.

Furthermore, Equation 19 should be valid for any distribution of mutational effects p. In the limit where the equilibrium lag is reached fast (i.e., when γ is large; Equation 6b), the moving-optimum model reduces to a model with constant selection for any focal allele (i.e., as in Hermisson and Pennings 2005).

Under constant selection, the average fitness will increase with probability θ and decrease with probability 0. In the same way as for frequency dependent selection, it will remain constant with probability 1 − θ. Figure 1 illustrates these results and compares frequency dependent selection to constant selection for all values of θ.

The population-scaled selective advantage Ns was 100 for constant selection and 1000 for episodic selection.

This population is allowed to evolve under a constant selection pressure for mediating two separate responses.

Two-thirds of the NBS-encoding genes under selection were associated with domestication rather than improvement which may have been influenced by the perennial nature of the wild relatives of sorghum, in contrast to the annual life-cycle of the majority of cultivated types, through increased plant longevity in the face of constant selection pressure for disease resistance.

Across the sets of simulations, initial haplotype frequencies at the beginning of the experiment were accurately reproduced, with a mean absolute error in the inferred frequency of 7×10−3 for constant selection coefficients and 1.5×10−2 for exponential selection coefficients.

The population-scaled rate of advantageous mutation Nμ a was 20 per generation for constant selection and 0.008 per generation for episodic selection.

As shown in Fig. 6, stochastic recruitment results in largely constant selection differentials, except for short-term irregularities that are not correlated with population abundance (Pearson product-moment correlation coefficient r = −0.09, with P = 0.35).

Results for systems with exponentially distributed selection coefficients were substantially better at higher mutation rates than those for constant selection coefficients, a constant selection coefficient allowing for multiple equally fit haplotypes to arise within each marker population.

For constant selection, the fitness distribution of a mutant is simply a one dimensional distribution around d.