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Then the two datasets were selected to detect site-specific positive selection and purifying selection.
Additional datasets were selected to test the results of our work.
The 29 samples present in the phase-known and the phase-predicted datasets were selected to test Haplous performance, and from these samples we created two datasets, one having phase-known and the other phase-predicted haplotypes.
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For illustration purpose, two publicly available credit datasets are selected to demonstrate the effectiveness and feasibility of the proposed weighted LSSVM classifier.
Two popular face datasets are selected to evaluate the experimental discretization performance in this section: This employed dataset is a subset of the FERET face dataset [29], in which the images were collected under varying illumination conditions and face expressions.
One of the datasets was selected to illustrate the flow of a typical analysis.
All four BP and NBP features in the original feature dataset were selected to the optimal feature set, which revealed that BP and NBP features contribute mostly to distinguish RNA-binding proteins from nonbinding ones.
Second, joints with high discrimination for the whole dataset are selected to design feature.
This dataset was selected to determine if it was possible to distinguish the difference between a real dataset that did not undergo a significant perturbation and random responses.
When multiple probes were mapped to the same GeneID (EntrezGene identification number), the one with the highest variance in a particular dataset was selected to represent the GeneID.
The RDP sequence with the highest number of corresponding pyrosequencing reads, in the entire dataset, was selected to represent each phylotype.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com