Main Content
Perform Sensitivity Analysis
Determine which model components are sensitive to specific conditions
or drugs using local and global sensitivity analyses such as Sobol
indices, elementary effects, and multiparametric GSA
Perform sensitivity analyses to investigate the influence of model parameters and initial conditions on model behavior. Compute Sobol indices or elementary effects and perform multiparametric global sensitivity analysis (MPGSA) to gain insights into relative contributions of individual parameters that contribute most to the overall model behavior. You can also perform local sensitivity analysis (LSA) to analyze the effect of one model parameter at a time, while keeping the other parameters fixed.
Apps
SimBiology Model Builder | Build QSP, PK/PD, and mechanistic systems biology models interactively (Since R2020b) |
SimBiology Model Analyzer | Analyze QSP, PK/PD, and mechanistic systems biology models |
Functions
Objects
Topics
Sensitivity Analysis and Simulation Basics
- Sensitivity Analysis in SimBiology
Sensitivity analysis lets you explore the effects of variations in model quantities (species, compartments, and parameters) on a model response. - Model Simulation
Simulate dynamic models using various solvers. - Accelerating Model Simulations and Analyses
Accelerate simulation or analysis by converting a model to compiled C code.
App Workflow
- Find Important Tumor Growth Parameters with Local Sensitivity Analysis Using SimBiology Model Analyzer
Perform local sensitivity analysis to find important parameters for tumor growth. - Find Important Parameters for Receptor Occupancy with Global Sensitivity Analysis Using SimBiology Model Analyzer
Perform GSA analyses, such as Sobol indices, elementary effects, and multiparametric GSA, to find important model parameters in a target-mediated drug disposition model.
Programmatic Workflow
- Perform Global Sensitivity Analysis by Computing First- and Total-Order Sobol Indices
Find sensitive parameters to tumor growth using Sobol indices. - Perform GSA by Computing Elementary Effects
Find sensitive parameters to tumor growth using elementary effects. - Perform Multiparametric Global Sensitivity Analysis (MPGSA)
Find sensitive parameters to receptor occupancy by performing multiparametric global sensitivity analysis. - Calculate Sensitivities Using sbiosimulate
Perform local sensitivity analysis on a G-protein model to find parameters that influence the amount of active G protein.