CNApy

CNApy implements computational analyses of metabolic networks using the Constraint-based Reconstruction and Analysis (COBRA) framework to enable flux balance analysis, elementary mode analysis, and related constraint-based methods for network design and optimization.

Key Features:

• COBRA methodology support: Implements a comprehensive range of standard and advanced Constraint-based Reconstruction and Analysis (COBRA) techniques.
• Flux Balance Analysis (FBA) and elementary mode analysis: Provides methods for steady-state flux optimization (FBA) and pathway-level decomposition via elementary mode analysis.
• Modular extension capability: Employs a modular architecture that enables embedding additional computational functionalities and extensions.
• Python implementation: Developed in Python to integrate with Python-based computational workflows and libraries.

Scientific Applications:

• Metabolic Network Reconstruction: Supports reconstruction and analysis of genome-scale metabolic networks using constraint-based approaches.
• Network Design and Optimization: Facilitates design and optimization of metabolic pathways for biochemical production and engineering.
• Comparative Metabolomics: Enables comparative analyses of metabolic network properties across organisms or conditions using COBRA methods.

Methodology:

Computational methods explicitly include the Constraint-based Reconstruction and Analysis (COBRA) framework, flux balance analysis (FBA), and elementary mode analysis.