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Calculate Sensitivities

Determine which model components are sensitive to specific conditions or drugs

Functions

sbiosimulate Simulate SimBiology model
sbioaccelerate Prepare model object for accelerated simulations
sbiosampleparameters Generate parameters by sampling covariate model (requires Statistics and Machine Learning Toolbox software)
sbiosampleerror Sample error based on error model and add noise to simulation data
addconfigset Create configuration set object and add to model object
getconfigset Get configuration set object from model object
createSimFunction Create SimFunction object

Classes

SensitivityAnalysisOptions Specify sensitivity analysis options
SimData object Simulation data storage
Configset object Solver settings information for model simulation
SolverOptions Specify model solver options
RuntimeOptions Options for logged species
CompileOptions Dimensional analysis and unit conversion options
SimFunction object Function-like interface to execute SimBiology models
SimFunctionSensitivity object SimFunctionSensitivity object, subclass of SimFunction object

Examples and How To

Desktop Workflow

Identify Important Network Components from an Apoptosis Model Using Sensitivity Analysis

This example shows how to identify important network components in an apoptosis model using sensitivity analysis in the SimBiology® desktop.

Programmatic Workflow

Calculate Sensitivities

This example uses the model described in Model of the Yeast Heterotrimeric G Protein Cycle to illustrate SimBiology sensitivity analysis options.

Concepts

Sensitivity Calculation

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.

Model Simulation

SimBiology lets you simulate the dynamic behavior of a model.

Choosing a Simulation Solver

SimBiology uses a solver function to compute solutions for a system of differential equations at different time intervals during model simulation.

SUNDIALS Solvers

SUNDIALS is an advanced computational package for solving systems of nonlinear algebraic equations, ODE, or DAE systems.

Stochastic Solvers

The stochastic simulation algorithms provide a practical method for simulating reactions that are stochastic in nature.

Accelerating Model Simulations and Analyses

You can accelerate the simulation or analysis by converting the model to compiled C code.

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