matlab-simulate-simbiology-model

Simulating SimBiology models generates deterministic ODE or stochastic SSA time-course outputs for prediction and parameter studies. You can run model behavior simulation, dose scenario exploration, and sensitivity analysis across observables and time points.

Deterministic simulation uses ODE solvers for standard continuous dynamics, while stochastic simulation applies the SSA algorithm for systems with noise or low molecule counts. Both produce time-course outputs for model behavior prediction and parameter influence studies.

Sensitivity analysis quantifies influential parameters using Sobol, Morris, or local methods via configset settings. Parameter sweeps and dose scenarios are configured using SimBiology.Scenarios to compare variants and parameter changes across observables and time points.

Stochastic SSA simulation requires MassAction-only reaction kinetics to function correctly. Non-MassAction reactions violate SSA solver constraints and cause simulation failures, so you must convert reaction kinetics before running stochastic trajectories for low molecule count systems.

Observables require honoring element-wise operator rules to calculate correctly, and StatesToLog configuration must be adjusted to capture constant parameters during simulation. Proper configuration ensures accurate time-course outputs for downstream prediction and what-if analysis.

SimBiology Scenarios require proper construction without arithmetic operations on Scenarios objects. Additionally, sensitivity option resets, MaximumWallClock timeouts, and unit conversion via TimeUnits must be correctly handled to avoid simulation failures and incorrect results.