MASSef

MASSef estimates and reconciles kinetic parameters for mass-action enzyme models to enable accurate pathway-scale kinetic modeling of metabolism.

Key Features:

• Robust Parameter Estimation: Estimates macroscopic (Km, kcat, Ki, Keq, n_h) and microscopic rate constants for diverse reaction mechanisms represented by mass-action kinetics.
• Handling Parameter Uncertainty: Quantifies and manages parameter uncertainty arising from limited or conflicting kinetic data.
• Integration of Historical Data and Machine Learning Estimates: Integrates kinetic values from literature and machine-learning estimation tools to assemble comprehensive parameter sets.
• Reconciliation of Inconsistent Data: Identifies and reconciles inconsistencies between in vitro experimental data and in vivo enzyme behavior to ensure model consistency.
• Pathway-Scale Model Assembly: Parameterizes enzyme modules and assembles them into pathway-scale kinetic models for metabolic analysis and strain design.

Scientific Applications:

• Systems Biology: Enables construction of detailed kinetic metabolic models to predict cellular behavior under varying conditions.
• Synthetic Biology and Metabolic Engineering: Supports design and optimization of engineered strains by parameterizing pathways and predicting production performance.
• Biotechnology and Industrial Bioprocessing: Applied to develop and optimize metabolic pathways for biofuel production and pharmaceutical synthesis.

Methodology:

Collects and integrates kinetic data from historical experiments and machine-learning estimates, applies computational parameter estimation methods that account for uncertainty and reconcile inconsistent data, and assembles parameterized enzyme modules into pathway-scale mass-action kinetic models.