MetGENE

MetGENE aggregates gene-centric metabolomics information to integrate genes, pathways, reactions, metabolites, and references to metabolomic studies for research use.

Key Features:

• Gene-Centric Aggregation: Focuses on genes encoding proteins directly involved with metabolites to emphasize gene–metabolite associations.
• Hierarchical Data Retrieval: Retrieves and organizes information across genes, related pathways, reactions, metabolites, and references to metabolomic studies.
• Repository Aggregation: Systematically aggregates data from established biological repositories to centralize relevant metabolomics knowledge.
• Contextual Filtering Options: Provides filters by species, anatomical tissue type, and specific conditions such as diseases or phenotypes to contextualize results.
• Computable Data Formats: Exports information in computable formats such as JSON to enable integration with other omics analyses.

Scientific Applications:

• Mechanistic Studies: Supports reconstruction of networks and development of quantitative models to investigate biological mechanisms.
• Diagnosis and Treatment Development: Aids identification of biomarkers and therapeutic targets by linking gene functions with metabolic pathways.
• Disease Monitoring: Enables contextualized molecular-level monitoring of disease progression and response to treatment based on condition-specific data.

Methodology:

MetGENE uses a knowledge-based approach that systematically retrieves data from established repositories, organizes information hierarchically (genes, pathways, reactions, metabolites), and applies contextual filters such as species, tissue type, and disease/phenotype.