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Scores for the genes outside a pathway are then calculated by drawing random samples from the background distribution.
In this study, we use a fully Bayesian inference based on analysis of posterior distribution of the model parameters by drawing random samples via MCMC simulation techniques.
For each positive set, a negative set of equal size was synthesized by drawing random samples from the list of all interactions, excluding those in that positive set.
These trajectories are obtained by drawing random samples from the so-called Reaction Probability Density Function (RPDF) [ 6, 7] through the ITS.
In a Monte Carlo simulation, 100 datasets were simulated by drawing random samples for the PK parameters from the identified distributions for inter-individual variability, inter-occasion variability, and residual variability.
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The nomadic camps were selected by drawing random numbers.
Second, we compared the genotype frequencies within the disease sample with the pooled carriage sample by drawing 1000 random samples of 51 isolates (with replacement) from the 147 carriage isolates and comparing the frequency of each clonal complex in these random samples with that observed in the disease sample.
First, we varied the total size of the cohort by drawing simple random samples of 50% (condition 1) and 20% (condition 2), 100 times each, without replacement.
Hence the closest we could come to a rigorous quasi-experiment was by drawing stratified random samples from these 26 successful sites and the remaining 70 unsuccessful sites.
Then the actual number of clusters for the first snapshot,, is determined by drawing a random sample from this pdf.
From this marginal distribution, the intended snapshot power,, is determined by drawing a random sample from this pdf.
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by drawing random examples
by making random samples
by drawing random variables
by drawing different samples
by updating random samples
by drawing venous samples
by drawing random numbers
by drawing many samples
by using random samples
by drawing independent samples
by drawing random values
by drawing random fragments
by generating random samples
by drawing random patterns
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