AMIGO2

AMIGO2 provides computational methods for dynamic modeling, parameter estimation, identifiability analysis, optimal experimental design, multi-objective optimal control, and dynamic flux balance analysis of biological systems.

Key Features:

• Iterative Identification Procedure: Performs local and global sensitivity analyses, parameter ranking (local and global), parameter estimation, identifiability analysis, and optimal experimental design in an iterative workflow.
• Non-Linear Optimization: Solves non-linear optimization problems constrained by algebraic and dynamic equations for parameter estimation and optimal experimental design.
• Advanced Numerical Methods: Implements state-of-the-art multi-objective global optimizers for complex optimization problems.
• Model-Based Metabolic Engineering and Drug Dose Optimization: Formulates metabolic engineering and drug dose optimization tasks as multi-objective optimal control problems.
• Dynamic Flux Balance Analysis: Supports dynamic flux balance analysis to analyze temporal behavior of metabolic networks.

Scientific Applications:

• Parameter Estimation: Estimates parameters in dynamical biological models using constrained non-linear optimization and global optimizers.
• Optimal Experimental Design: Designs experiments to maximize information gain through optimal experimental design methods.
• Identifiability Analysis: Assesses parameter identifiability via local and global analyses.
• Metabolic Engineering and Drug Development: Optimizes metabolic pathways and dosing regimens using multi-objective optimal control and dynamic flux balance analysis.

Methodology:

Computational methods explicitly include local and global sensitivity analyses, parameter ranking, parameter estimation, identifiability analysis, optimal experimental design, non-linear optimization constrained by algebraic and dynamic equations, state-of-the-art multi-objective global optimizers, dynamic flux balance analysis, and advanced simulation approaches.