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Although Equation 2 is sufficient for breeding value prediction, to define a realized relationship matrix, a convention is needed concerning the scaling of the matrix.

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For this study, we used the standard deviation (STD) of ensemble predictions to define the applicability domain.

The RTX sequence was evaluated using a consensus web-based tool, AmylPred, which utilizes multiple parallel prediction algorithms to define regions of sequence that may contribute to amyloid or amyloid-like packing and association.

For evaluating protein complex prediction, we need to define how well a predicted complex which consists of a set of protein members, matches an actual complex, which is another set of protein members.

This work presents Constraint-based Flux Analysis (CBFA), an open-source software application for flux analysis in metabolic models that implements several methods for phenotype prediction, allowing users to define constraints associated with measured fluxes and/or flux ratios, together with environmental conditions (e.g. media) and reaction/gene knockouts.

The results of these predictions were used to define three scores that characterise targeting motifs in a protein: Mitochondrial score sM = 1 if TargetP predicts a mitochondrial targeting peptide, sM = 0 otherwise.

Our precise CO breakpoint predictions enabled us to define blocks of the genome that were uninterrupted by COs in any F2 individual in both the wild-type and recq4a F2 populations.

In order to define prediction models, five variables were identified and included in the model.

A stepwise regression analysis was used in this research to define prediction models that could be used to forecast individual future growth changes of the mandible.

The NPV tended to be high (>0.899) at all the various prediction value thresholds chosen to define the two classes.

In this work, we launched our investigation of constructing high-quality, resource-efficient hBMSC prediction models by aiming to define essential morphology parameters.

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