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To assess the statistical significance of the enrichment of different subcellular compartment pairs in the predicted rice interactome, we used a randomization algorithm.
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As a control, multiple sequence alignment blocks were shuffled using a randomization algorithm that takes care not to introduce randomization artifacts and produces random alignments of the same length, base composition, overall conservation, local conservation pattern, and gap pattern as the input alignment [44].
Inmates meeting inclusion criteria were allocated randomly to one of two study groups using a randomization algorithm.
We used a random number algorithm for randomization.
Eligible patients from these practices were arranged in random order for each practice using a computerized randomization algorithm, and the first 13 patients from each practice were selected to achieve a sample size of 104.
To recruit adolescent and parent participants, a random sample of 100 adolescents aged 11 – 18 years were identified from each practice using a computer randomization algorithm applied to electronic patient records.
A randomization algorithm used a blocking scheme to ensure a balance between the vaccines, and stratified the study groups (aged ≥65 years) by age (65 74 years [65%] and ≥75 years [35%]).
To determine the significance of the observed motifs, motif detection was repeated on one thousand randomized networks using a strict randomization algorithm.
Treatment group assignments were determined using a dynamic randomization algorithm within the interactive voice response system.
A randomization algorithm is then applied to each datapoint, using the EXCEL "RAND" function, to allow the simulated data plots to appear visually similar to real data.
The randomization will be achieved by means of a computer-generated assignment system (a randomization algorithm).
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