KEGG Metabolic Pathways Modeled as a Directed Relation Network

KEGG Metabolic pathways modeled as a directed relation network. A large number of pathways were extracted from KEGG XML and modeled into a graph where enzymes and genes are nodes and substrate/product compounds are edges. The dataset was created by Muhammad Naeem and Sohail Asghar and is licensed under CC-BY-4.0.

Use Cases

• Analyze the topological structure of metabolic networks based on the described graph model.
• Train graph machine learning models on biochemical interaction data.
• Study enzyme-gene relationships within metabolic pathways.
• Compute and compare network features for different metabolic pathways.

Strengths

• Explicitly states no missing values.
• Derived from the authoritative KEGG database.
• Includes a variety of computed network features.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

KEGG (Kyoto Encyclopedia of Genes and Genomes) database.

Collection Method

Pathways were extracted from KEGG XML and modeled into a graph using Cytoscape to compute network features.

Time Range

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Freshness

Last updated date is unknown.

Geography

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