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The Representative Proteome datasets were created to provide the best possible coverage of protein information content while both reducing the number of sequences and providing a more even sampling of sequence space.
Independent variables with more than 2% of values missing were imputed, and 50 concatenated datasets were created to reduce any potential bias caused by rounding.
A variety of datasets were created to address this question and were analysed using Bayesian and two methods of protein maximum-likelihood phylogeny.
Two false positive datasets (SLiMDoM- and Domino-False Positive Datasets) were created to be specific controls for each of the aforementioned true positive datasets and the same procedure was applied to each.
As such, multivariate Poisson regression models of mortality rate ratios for the 10-year dataset as well as each of the simulated error datasets were created to investigate the extent to which errors altered well-established associations between the above parameters and mortality.
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This dataset was created to provide a benchmark for the forensic analysis of images and videos.
The second dataset (Non-overlapping intraspecific dataset) was created to remove redundant information from the previous dataset.
A minimal NARA dataset was created to contain data that all registries could deliver (Havelin et al. 2009).
In our implementation of RFML, a temporary validation dataset is created to build each regression tree, and is chosen as a randomly selected set of 250 samples left out of the full training dataset.
This dataset was created to check if the method was able to detect signals of "unexpected" species, which would possibly not have a reference genome included in the initial mapping step.
For the GPS population, three different datasets of performances were created to obtain BLUP evaluations, leading to three scenarios to account for genomic pre-selection at the national level: 1. BLUP evaluations included only one type of phenotypes for the YS, i.e. the simulated performances of their daughters.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com