CAMND

CAMND performs decomposition and comparative analysis of genome-scale metabolic networks to identify functional metabolic modules.

Key Features:

• Decomposition Methods: Implements 10 distinct methods for decomposing metabolic networks into modules.
• Datasets: Supports analysis across 9 different datasets for comparative studies.
• Evaluation Criteria: Employs 12 evaluation criteria, including ten previously defined criteria plus two novel criteria based on Chebi ontology and Co-expression_of_Enzymes.
• Visualization: Uses Gephi to visualize modules resulting from network decomposition.
• Extensibility: Permits incorporation of new datasets and evaluation criteria for extended analyses.
• Comparative Analysis: Facilitates direct comparison between novel decomposition methods and previously developed approaches.
• Implementation: Implemented in Python.

Scientific Applications:

• Module identification: Identifies functional modules within metabolic pathways.
• Disease mechanism analysis: Aids analysis of metabolic alterations underlying disease mechanisms.
• Drug target discovery: Supports identification of candidate metabolic drug targets.
• Metabolic engineering: Informs metabolic engineering strategies by revealing pathway organization.
• Methodological benchmarking: Enables benchmarking and optimization of decomposition methods.

Methodology:

Apply 10 decomposition methods to genome-scale metabolic networks across 9 datasets, evaluate results using 12 criteria (including Chebi ontology and Co-expression_of_Enzymes), compare decomposition methods, and visualize modules with Gephi; implemented in Python.