The combinatorial testing was originally proposed in order to reduce the number of test data required to verify the interoperability among the functions of a system, based on a combinatorial method used in mathematical constructions for statistical experiments [13, 20].
Even the largest available database of somatic mutations, that for p53, is not large enough for some statistical experiments.
The solution of he problem relies on statistical experiment design for he stochastic characterization of he system.
The solution of the problem relies on statistical experiment design for the stochastic characterization of the system.
In this study, Taguchi robust design was employed as a statistical experiment design for coating of magnesium powder with azidodeoxy cellulose nitrate via solvent/non-solvent technique.
For our statistical experiments, we kept only the terms with no less than five mapped genes within the set of weights considered and hence the number of processed terms varied for each realization of sampling (see below).
With SVM, trial design, and other statistical methods, experiments for CHO cells become simplified and credible.
This model of statistical experiment is valid for competitive methods with randomization of samples, such as: GSEA, SAFE.
A statistical experiment design was employed for materials testing and the development of data-driven models.
Furthermore, our proposed methodology can be used for making statistical inferences in experiments for which replicates are not available.
