SimBiology 3.1

Analyzing a Model

SimBiology provides functionality that lets you gain insight into your model via parameter estimation, sensitivity analysis, and parameter scans.

Parameter Estimation

With SimBiology you can fit the response of your model to experimental data. You can fit parameters with MATLAB or by using optimization algorithms in Optimization Toolbox™. SimBiology also lets you fit parameters to population data sets using nonlinear mixed-effects models in Statistics Toolbox™.

Sensitivity Analysis

SimBiology lets you calculate the sensitivities of all system species relative to the specified parameters and species’ initial conditions. This analysis helps you better understand the behavior of the network and lets you determine parameters of highest importance. Sensitivities to various initial conditions enable investigation into the behavior of the network across populations.

SimBiology provides several options for analyzing sensitivities. For example:

• Computed sensitivities can be normalized or presented without normalization.
• Sensitivities can be computed relative to a user-specified set of parameters, species’ initial conditions, or both.

Parameter Scans

SimBiology allows you to perform parameter scans to visualize the dynamic behavior of the model over a range of parameter values. You can also perform scans on species and compartment values.

Parameter fitting in SimBiology. SimBiology lets you fit the response of your model to population data sets using nonlinear mixed-effects models in Statistics Toolbox (near left). Click on image to see enlarged view.