The animal models used currently (the mouse HSV-2 model, the rabbit vaginal irritation index, and the macaque SIV model) have substantial differences from humans.
The results presented here are exciting and important, as they demonstrate that degeneracy and the applied event model have substantial impact on the histories inferred and, hence, on the resulting biological conclusions.
From the experimental validations regarding the forces, frequencies, cavity visualizations and velocity distributions, the PANS model is shown to improve the predictive capability considerably, in comparison to the standard k − ɛ model, and also, it is observed the value of f1 in the PANS model has substantial influence on the predicting result.
These indices indicate that this model has substantial predictive power.
Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions.
Our empirical analyses of two different datasets, representing both prokaryotic and eukaryotic data, indicate that use of a complete event model has substantial impact on the events inferred and, hence, the resulting biological conclusions.
Following Burnham and Anderson [ 68], we considered that a model had substantial empirical support if its ΔAIC was lower than 2. The number of alleles for each microsatellite locus varied between 8 and 21, whereas observed heterozygosity varied between 0.70 and 0.91 (Table 2).
The alternative model implementation revealed that untested assumptions in the original model could have substantial influence on simulated outcomes.
However, most CHI model systems have substantial caveats, including the high incidence of skull fracture (necessitating euthanasia of the animal) and highly variable outcomes between laboratories.
