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Modeling approaches can be used to evaluate the most appropriate scale over which to sample and predict pathogen and HAB concentrations based on their variability in time and space.
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One could compare, for example, drug treated samples to untreated samples and predict pathways targeted by the compound.
With this information it is possible to infer the history of the sample and predict its behaviour.
A key feature of SCHEMA chimera families is their amenability to a "sample, model, and predict" operation that allows one to characterize members of a small chimera sample set and use those data to construct models that accurately predict the properties of every member of the family.
During LOOCV, each sample in the dataset was used as a test sample and predicted based on the model trained with the other samples.
Characterization of gold minerals and carriers in composite ore sample can be used to diagnose, and predict metallurgical response, identify potential problems, and help in the design of a more robust metallurgical testwork program.
In a separate study, Fagerberg et al [8] utilized molecular dynamic and simulated annealing to sample the conformational space and predict binding of peptides to MHC class I molecules.
Micro tensile tests were performed and compared with finite element simulations to estimate the applied forces on the sample and to predict the functionality of different grid designs.
This strategy has been used to analyze serum samples and to predict the calcium concentration in blood serum.
The regression coefficients were applied to the validation sample and a predicted probability of readmission was generated for each individual from the coefficients.
Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients.
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