REDEMPTION

REDEMPTION: Incremental Parameter Estimation and Ensemble Modeling for ODE-Based Biological Systems

REDEMPTION performs parameter estimation for ordinary differential equation (ODE) models of dynamic biological processes using an incremental parameter estimation strategy formulated as a nested optimization problem.

Key Features:

• Incremental Parameter Estimation (IPE): Formulates parameter estimation as a nested optimization problem, enabling efficient estimation in complex biological models with numerous reactions and limited measurable species.
• Ensemble Modeling: Identifies ensembles of parameter sets that achieve satisfactory goodness-of-fit to experimental data, capturing multiple plausible solutions.
• Parallel Computing Integration: Supports numerical parallelization via MATLAB Parallel Computing Toolbox to accelerate computation for large datasets and complex ODE models.

Scientific Applications:

• Systems Biology Modeling: Estimates parameters and constructs ensembles for ODE-based models to support hypothesis testing, experimental design, and analysis of complex biological networks.

Methodology:

Solves a nested optimization problem using incremental parameter estimation to iteratively refine parameter values and improve model fit. Ensemble modeling identifies multiple parameter combinations consistent with observed data, representing variability in biological systems.