|Simulate SimBiology model|
|Prepare model object for accelerated simulations|
|Generate parameters by sampling covariate model (requires Statistics and Machine Learning Toolbox software)|
|Sample error based on error model and add noise to simulation data|
|Create configuration set object and add to model object|
|Get configuration set object from model object|
|Get 3-D sensitivity matrix from SimData array|
|Create SimFunction object|
|Specify sensitivity analysis options|
|Simulation data storage|
|Solver settings information for model simulation|
|Specify model solver options|
|Options for logged species|
|Dimensional analysis and unit conversion options|
|Function-like interface to execute SimBiology models|
|SimFunctionSensitivity object, subclass of SimFunction object|
This example shows how to identify important network components in an apoptosis model using sensitivity analysis in the SimBiology® desktop.
This example uses the model described in Model of the Yeast Heterotrimeric G Protein Cycle to illustrate SimBiology sensitivity analysis options.
Calculating sensitivities lets you determine which species or parameter in a model is most sensitive to a specific condition (for example, a drug), defined by a species or parameter.
Simulate dynamic models using various solvers.
Accelerate the simulation or analysis by converting the model to compiled C code.