In order to evaluate our game theory modeling approach, we used a queuing analysis that is used in [22].
Using this traffic modeling approach, we propose some probabilistic envelope processes that can be used to represent the resource demand of a traffic stream in performance evaluation studies.
Thirdly, based on the implicit calculus equation modeling approach, we introduced the concept of fundamental solution on fractal and consequently defined the fractal differential operator to describe various mechanical behaviors of fractal materials.
Within our modeling approach, we have also introduced novel in silico experiments such as mosaic analysis, where the behavior of mutant and neighboring cells can be analyzed.
Using this novel modeling approach, we estimated SNP frequency in protein-coding (mRNA) and non-coding transcripts (e.g., small RNAs).
An exactly reduced version of the crosstalk model was generated using the reduced order modeling approach we introduced above.
Using this efficient modeling approach, we then introduced the framework for performing perturbation experiments on gene regulatory networks.
The linear regression modeling approach we used in 2009 had a shortcoming in that it attempted to determine the regulation structure for each target gene independently, while it is well known that genes that share the same expression pattern are likely to be involved in the same regulatory process, and therefore share the same (or at least a similar) set of regulators.
The reason for this occasional inability of our method to prevent over-fitting the models resides in its using successive steps of model selection, instead of comparing all possible models at once, which is intractable with the piece-wise modeling approach we are using.
After calibrating the model by a data-based modeling approach, we used it to study the following question: if cells are exposed to osmotic stress, what is the minimum duration of the stress that is necessary for cells to induce a Hog1 response?
