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The proposed tool can easily take up billions of molecules for classification.
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For classification of molecules that melt and decompose we used bagging validation [49].
The authors concluded, however, that the models based on the average of chemist estimations may be useful for classification of molecules.
We introduce a computational method for classification of individual DNA molecules measured by an α-hemolysin channel detector.
This kind of retrospective virtual screening is performed by using encoded molecule data and a neuro-fuzzy methodology for classification, feature selection, and rule generation.
As an extension of this classification, the number of molecules involved in the rate-limiting step of a several-stage reaction also can be used for classification of the overall reaction.
Alternatively, information on the activity and amount of intracellular signaling molecules was used to build PLSR model for prediction of cellular responses and selection of the most informative for classification subset of signals (feature selection) [ 5].
Normalized ΔCt data were used for classification.
This concatenated feature was used for classification.
‡p<0.01 for classification index.
p = 0.008 for classification index.
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