ASPASIA

ASPASIA performs automated parameter alteration, timed intervention simulation, and local and global sensitivity analysis on SBML-encoded systems biology models to evaluate how parameter changes and interventions affect system behavior.

Key Features:

• Automated Parameter Alteration: Automates alteration of parameters in SBML models to simulate different biological scenarios and interventions.
• Intervention Modeling: Applies interventions at specified time points within model simulations, accommodating state- and time-dependent perturbations.
• Sensitivity Analysis: Implements both local and global sensitivity analysis techniques to assess how parameter changes influence model outcomes.
• Model Generation and Modification: Generates and modifies models using SBML solver outputs and applies interventions once a steady state has been achieved.

Scientific Applications:

• Systems biology intervention analysis: Enables analysis of how interventions and parameter perturbations affect biological processes in SBML-encoded models.
• Th17-cell plasticity investigation: Used with an SBML model of Th17-cell polarization to predict that promoting the Th1-associated transcription factor T-bet drives Th17 cells toward an IFN-γ-producing phenotype.

Methodology:

Generates a baseline model using SBML solver outputs to set initial conditions and steady state, applies interventions at defined time points, performs automated parameter alterations, and conducts local and global sensitivity analyses.