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To correct for multiple comparisons, a Monte Carlo simulation was conducted to determine the random distribution of voxel cluster sizes for a given threshold [60].
The Random TFBS occurrence parameter is combined with the Select background parameter to determine the background sequence type (random, core, promoter or conserved promoter), and together they determine the random TFBS occurrence rate.
Determine the "random forest importance" (RFI) by 50 runs of the machine learning algorithm.
In order to determine the random occurrence of enriched GO-terms, we used our experimental expression array data set and randomized the gene names associated with expression values using the "sample" function in R, and used in the following context: sample x, length(x), replace = FALSE, prob = NULL) where x is a vector of gene IDs.
The following three steps were performed so as to obtain the ultimate prediction model: Determine the "random forest importance" (RFI) by 50 runs of the machine learning algorithm.
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An experimental investigation is performed to determine the random-incident scattering coefficients of wooden diffuser structures characterized by different materials, geometrical designs, groove depths and baffle features.
A1 California Plays Alphabet Game Even the alphabet is getting an official makeover as a state elections official, helped by a part-time percussionist from a Latin jazz band, determined the random order of the candidates on the Oct. 7 ballot on whether to recall Gray Davis.
A state elections official, assisted by a part-time percussionist from a Latin jazz band, determined the random alphabetical order of the candidates on the Oct. 7 ballot under the glare of klieg lights with a floor-to-ceiling display as a backdrop.
Due to this property, it is necessary to rethink the approach in determining the random values.
PM has performed the power calculations and determined the random order in which the different centres will switch from control to intervention period, and will perform the statistical analyses.
The inter-individual variability of model parameters was described by an exponential equation, according to: P 1i = θ 1 ⋅ exp (η i ), where θ1 is the population (typical) estimate for parameter P1, P1i is the individual estimate and ηi determines the random deviation of P1i from P1.
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