We propose an eigenvalue based method for efficiently testing identifiability of large ordinary differential models and compare this approach to three existing ones.
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.
While providing a more formal and statistically-based method for test selection in lesion symptom analyses, when used on an extensive battery of behavioural assessments, PCA also allows derivation continuous, orthogonal multidimensional measures of aphasic deficits.
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.
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.
For this reason, we consider the PCA based method to be inappropriate for the identifiability testing of the three treated pathways.
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.
We measured NaCl taste thresholds using a conditioned taste aversion (CTA)–based method optimized in our laboratory for high-throughput testing of mice.
For comparison, we also tested the Majority Rule (MR) method by Schwikowski et al. [14], a simple domain based method, and orthology based method.
