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Five replicates of each dataset were generated and analyzed with a generalized prior (g-prior) of varying weight.
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Due to the lack of suitable experimental data, a synthetic dataset is generated and used to investigate the validity of the procedure.
The content of this dataset is generated and kept updated by Ordnance Survey, the UK official mapping agency, and was made freely accessible for the first time in 2010.
A 23 gigabase (Gb) dataset was generated, and 297,955,888 raw reads were obtained.
For each replication, a new complete dataset was generated, and then the intended percentage of data was deleted.
Based on the selected features for each chromosome; a dataset is generated and is given to the predictive model (classifier) to evaluate the goodness of the chromosome.
A first dataset was generated and included: Comprehensive HH information including roster of all members (by age, sex, marital status, education, location (urban or rural), HH head) and socio-economic status.
In order to evaluate the quality of the PM metric and to compare its behavior to the other metrics, a large number of datasets were generated and analyzed.
Two hundred replicate bootstrap datasets were generated and used for evaluation of parameter estimate precision.
For each sample size, 100 datasets were generated and analyzed by IgC2N.
In our experiments, 100 bootstrap datasets were generated and ARACNe was used to generate a set of bootstrap networks.
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CEO of Professional Science Editing for Scientists @ prosciediting.com