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Only one candidate was validated out of the 14 tested with 21 primer pairs (Table 1).
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In total, 128 functionally important sSNVs were validated, out of which 119 were true-positive sSNVs and nine were false-positives.
This approach to projection was validated with out-of-sample posterior predictive checks, and compared favorably to the variable- r model in EPP 2011 [ 10].
This was validated by carrying out qPCR on selected genes and is exemplified by Sb01g021320.
The regression model was validated using hold-out cross-validation, with a 50% training sample and a 50% testing sample.
The feature selection and classification model was validated by leave-one-out cross-validation (LOOCV).
The developed score was validated by leave-one-out cross validation.
The model was validated using leave-one-out cross validation (LOOCV) statistical method.
The generated pharmacophore hypothesis was validated using leave-one-out and test set methods.
Each developed model was validated with the corresponding left out standard.
However all the predicted molecular markers need to be validated to rule out false positives and sequencing errors.
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