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Depending on the selected validation approach, compounds can even be predicted multiple times.
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When using a repetitive sampling scheme, like bootstrapping or a n-times repeated k-fold cross-validation, compounds are predicted multiple times by (Q SAR models trained on different subsets of the data.
Then using the available data we make the following predictions: (6) { y n − j − (k − 1 ),..., y n − j } → y ^ n − j + k, j = 0,..., k − 1 Thus in our method each day is predicted multiple times.
The list shows proteins that were correctly predicted multiple times In contrast, more than 50 prediction pairs from the chemogenomic approach were proteins associated with metabolism of drugs.
This is the hypothesis tested by the standard methods of analysis, including the study by Marguerat et al. But in addition, it can also be predicted that in multiple independent time course experiments, the peak of expression will always be at a similar time in the cell cycle.
Whether this approach would be successful is difficult to predict because only a modest fraction of the variability in endurance time could be predicted from our multiple regression model.
So the execution time can be predicted.
The process would involve multiple surgeries, and the results could not be predicted.
The change in slump flow by hauling time was also evaluated and was predicted with multiple regression equations.
Dizziness in older age was predicted by multiple factors.
As expected, several genes are predicted targets of multiple microRNAs.
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