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We run the program with two different values of the population size M (Table 6).
In Fig. 1, we present the evolution of dG and dS, and of the mean viral fitness, f, with the number of generations for different values of the population size, C. We employ M = 3 and the experimental fitness landscape (Methods).
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The parameter zones for the oscillation mode are drawn for three different values of the total population Y, while keeping (X=1).
Then using Sampling with expansion, we drew contour plots of Tajima's D for different values of the time at which population expansion started and of the population expansion factor under local and pooled samplings.
To explore which parameter values of the global expansion model will produce simulations with Tajima's D values similar to the observed values of Tajima's D in our C. grandiflora dataset, we used Sampling v.0.5 to draw contour plots of Tajima's D for different values of the time at which population expansion started and of the population expansion factor under local and pooled samplings.
We investigate the performance of RNS-based tolerance intervals for different values of the design parameters and various population shapes.
To establish the validity of a Gaussian approach to defining abnormal, it is essential to establish that a) the distribution of the variable measured conforms to a normal (Gaussian) distribution, and b) the population with the target disease has significantly different values of the measured variable, in comparison to a population without the disease.
The time evolution of the proportion of the infectious population for different values of the parameters p, α and β is analysed.
Figure 5 Evolution of the infected and total populations with different values of the parameter ε used to generate the vaccination function.
We compare outcomes in these 2 populations for different values of the reproductive number R. We define R as the average number of secondary cases produced by a typical primary case in a population with a certain level of preexisting partial immunity.
Representative examples of distributions of beneficial and deleterious fitness effects (B or D in the first column) for optimized and adapting populations and two different values of the mutation rate in each case.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com