We propose an eigenvalue based method for efficiently testing identifiability of large ordinary differential models and compare this approach to three existing ones.
Section V describes a simulation experiment to investigate power and Type I error, using a bootstrap-based method for testing omnibus significance.
The REACTIN algorithm applies a similar strategy as SAM, while the modified method is similar to the test based method for identifying differential expressed genes.
For SVM, we experimented several kernels (including Radial Basis Function kernel and Polynomial kernel) and different values for parameter C. In Rotation Forest, different tree based methods for the ensemble approach were tested, varying their specific parameters in each case.
The ordinary t-test is provided as a reference for the improvement of any t-test based method, which DFC test and CAT test clearly are.
These include phenotypic culture based methods, tests for gene mutations and tests based on bacteriophage replication.
For this reason, we consider the PCA based method to be inappropriate for the identifiability testing of the three treated pathways.
Recently, many studies have demonstrated the significant advantages of loop-mediated isothermal amplification (LAMP) based methods over serological tests and PCR for rapid detection of microbial pathogens.
Taken together, we demonstrate that our method allows an objective and literature based method to evaluate the appropriateness of different statistical tests for a given experiment.
These criteria were based on OECD methods for testing [40] under the relevant conditions (OECD Methods 305, 308, 309, and 315).
Protocols for swim maze were based upon published methods for testing visual discrimination [ 38].
