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MetaboliticsDB: A Database of Metabolomics Analyses.

M Hasan Celik, Onurcan Ersen, Taj Saleh

    IEEE Transactions on Computational Biology and Bioinformatics
    |August 14, 2025
    PubMed
    Summary

    MetaboliticsDB is a novel database for storing and comparing metabolomics analysis results. It uses AI and network analysis to link metabolic data to diseases, aiding research into conditions like cancer.

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    Area of Science:

    • Metabolomics
    • Bioinformatics
    • Systems Biology

    Background:

    • Existing metabolomics databases lack comprehensive analysis and result management tools.
    • Current tools primarily superimpose metabolite data onto pathways, limiting deeper insights.
    • There is a need for integrated platforms for storing, comparing, and analyzing metabolomics results.

    Purpose of the Study:

    • To introduce MetaboliticsDB, a database and analytics platform for metabolomics data.
    • To enable storage, comparison, and advanced querying of metabolomics analysis results.
    • To integrate genome-scale metabolic network analysis and AI-driven disease association.

    Main Methods:

    • Development of a web-based database for metabolomics analyses.
    • Implementation of a genome-scale metabolic network-based analysis tool (Metabolitics) for flux analysis.
    • Integration of an advanced querying interface and AI-based models for disease association.

    Main Results:

    • MetaboliticsDB stores analysis results for 2,174 individuals and 40 diseases.
    • The platform provides biologically relevant metabolic network-level analysis.
    • AI models achieve high accuracy in associating metabolomics data with diseases.
    • Demonstrated utility via a Hepatocellular Carcinoma case study.

    Conclusions:

    • MetaboliticsDB offers a scalable architecture for comprehensive metabolomics data analysis.
    • The platform facilitates the identification of shared mechanisms across different conditions.
    • MetaboliticsDB enhances disease association studies through integrated AI and network analysis.