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A cross-check of all available methods is the best way to achieve maximal accuracy for polydisperse systems.
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We also estimated persistence of phase as a measure of prediction reliability of markers in one breed by those in another and found that markers less than 10 kb apart could be predicted with a maximal accuracy of 0.92 for Landrace with Yorkshire.
At best, we achieved a maximal accuracy of 80% and AUC of 0.88 for classifying distal group II alternative exon intron boundaries against the constitutive background in IMR90.
In H, we observed the same trend (data not shown) and obtained a maximal accuracy of 76.5% and AUC of 0.84 for classification of group I exon intron junctions against distal constitutive ones.
We obtained the best possible accuracy of classification with an AUC of 0.84 and maximal accuracy of 77.1% by using a filtering distance of 10 kb for determining the set of distal constitutive exon intron boundaries in IMR90.
The CC and HC-based models as standalones performed even worse with the maximal accuracy of 73.55% and 73.31% respectively.
The maximal accuracy of 84% could be found at a cut-off of 5.5.
The maximal accuracy is highest for the second codon position and lowest for the third.
Our maximal ROC curves can be substantially higher than those given by the beta distribution, which is an accurate proxy for multiple previous reports [ 10, 12, 13], indicating that the maximal accuracies of genetic prediction may be substantially higher than previously thought.
Magnetic resonance imaging (MRI), like CT, can separate visceral fat from subcutaneous fat and since there is no radiation involved, it can perform a total body scan for maximal accuracy and fat distribution.
The FNN analysis is a powerful machine-learning method for detecting, with maximal accuracy, significant combinations of characteristics that are associated with a particular attribute.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com