MetaDAG

MetaDAG generates and analyzes metabolic networks for specific organisms or datasets by retrieving data from the KEGG database.

Key Features:

• Reaction graph computation: MetaDAG computes a reaction graph that represents reactions as nodes and metabolite flow between them as edges.
• Metabolic directed acyclic graph (m-DAG) computation: The m-DAG simplifies the reaction graph by collapsing strongly connected components, significantly reducing the number of nodes while maintaining connectivity.
• Network generation from diverse inputs: MetaDAG generates metabolic networks from KEGG organisms or custom data including reactions, enzymes, or KEGG Orthology (KO) identifiers.
• Network visualization and download: The tool displays models on an interactive web page and provides downloadable files including network visualizations.

Scientific Applications:

• Taxonomy classification: MetaDAG successfully classified eukaryotic organisms from the KEGG database at the kingdom and phylum levels.
• Diet analysis and microbiome studies: MetaDAG accurately distinguished between Western and Korean diets and categorized individuals by weight loss outcomes based on dietary interventions.
• Synthetic metabolism generation: MetaDAG enables the generation of synthetic metabolisms for large-scale biological comparisons.

Methodology:

MetaDAG retrieves data from the KEGG database and computes two models: a reaction graph and a metabolic directed acyclic graph (m-DAG). The m-DAG is generated by collapsing strongly connected components of the reaction graph.