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In addition, in most of our models, we simulated 5,000 generations, but when simulations ran for 10,000 generations, the probability of speciation increased 1.2-fold (results not shown).
To determine the effect of integrating over uncertainty when sites in a sequence evolve and are analyzed under complex heterogeneous models, we simulated sequences with strong across-site heterogeneity in G+C content or site-specific changes in evolutionary rates (heterotachy, represented as different branch length sets for different sites [44]).
To evaluate the performance of dynamic marginal structural models, we simulated 1000 observational studies (n = 3,000) with CD4-dependent treatment initiation.
In order to validate further the meta-GRN models, we simulated mutations in the GRN and compared the resulting patterns with the reported phenotypes.
Using the effect size and variance component estimates from the longitudinal models, we simulated clinical trials to reflect the changes observed over time in the ADNI cohort for each biomarker/outcome combination with 7 years of follow up.
Under different demographic scenarios and the population epigenetic selection models, we simulated SMPs with the mean of θ m = 0.1 per site per generation, which is gamma distributed among the sites with α = 0.5.
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To validate our theoretical model, we simulated the works in Network Simulator NS-2 (release v2.31).
Using this model, we simulated soil development in a landscape.
The outcomes further indicate that the model we simulated are correct.
Using the relaxation model, we simulated numerically the time evolution of a rapid axisymmetric contraction.
In the modeling, we simulated plowed (PC) and snow-covered (SC) conditions.
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