MOFA

MOFA performs multi-objective optimization of flux distributions in genome-scale constraint-based metabolic models to quantify trade-offs among multiple biological objectives.

Key Features:

• Multi-objective analysis: Facilitates analysis of trade-offs among multiple biological objectives using genome-scale metabolic models (GSMs).
• Normalized Normal Constraint (NNC): Employs the Normalized Normal Constraint (NNC) method to normalize constraints and enable efficient multi-objective computation across objectives.
• Scalability: Supports multiple objectives with practical limits determined by computational resources (reported n ≤ 10).
• Integration with COBRA Toolbox: Implements as an add-on for the COBRA Toolbox in MATLAB to operate on constraint-based metabolic models.

Scientific Applications:

• Microbial metabolic trade-offs: Analyzes metabolic trade-offs in microorganisms such as E. coli using well-curated GSMs.
• Growth versus production optimization: Explores balances between growth, metabolite production, and other cellular functions.
• Resource allocation studies: Investigates organismal resource allocation under varying environmental conditions.

Methodology:

Performs multi-objective optimization on genome-scale constraint-based models (GSMs) using the Normalized Normal Constraint (NNC) algorithm.