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Pool-specific paired-end datasets were created by comparison to the pools-specific Titanium datasets using BLASTN and assigning each read to an individual pool.
Surrogate datasets were created by randomly shuffling the ISIs of the measured sequence.
Combined datasets were created by a combination of the ACT1, URA5, PLB1 and IDE sequences.
From each population 100 datasets were created by randomly selecting 80% of the data points from the original dataset.
Since the VM training and testing datasets were created by randomly assigning 4/5 of individuals for training and 1/5 for testing, we combined them for the purposes of creating a testing dataset for models built in the ARMA dataset.
In our study, 6 complete datasets were created by replacing missing values with simulated values.
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This new datasets are created by cropping the trace files into lengths based on the number of opcodes (1k-opcodes, 2k-opcodes etc).
Reanalysis datasets are created by assimilating ("inputting") climate observations using the same climate model throughout the entire reanalysis period in order to reduce the effects of modeling changes on climate statistics (Compo et al. 2011).
Suppose M datasets are created by a MI method assuming MAR.
One thousand sub-samples of the whole dataset were created by randomly discarding 20% of the observations.
The dataset was created by merging hospital databases with a provincial medication database.
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