
Quantitative metabolomics database
A database combining sample metadata and quantitative metabolite reference ranges into a standardized format for metabolomics research.
Overview
The Quantitative Metabolomics Database (QMDB) offers an essential resource for researchers striving to establish normal concentration ranges for metabolites. Recognizing the challenges posed by individual differences and varying internal and external factors, the database provides a standardized framework to define such ranges.
By merging sample metadata with quantitative reference ranges developed through Biocrates' standard technology, QMDB assists researchers in understanding metabolic differences amongst diverse populations, taking into account ethnicity, sex, and lifestyle variations.
Key Features of QMDB
- Access to ranges for over 620 metabolites, offering insights into the metabolomes of healthy subgroups.
- Characterization of user-defined control groups by comparison with QMDB, helping identify outliers in data sets.
- Reference control groups support deeper insights into data analysis and improve interpretations without needing extra controls.
- Conduct in silico studies, facilitating the identification of new metabolic signatures in QMDB subgroups and enabling hypothesis testing prior to live experiments.
- Participation in a data network, allowing users to compare their findings with community-generated data, contributing to and benefiting from an expanding database.
QMDB includes metabolite concentration data from human plasma samples sourced from individuals considered healthy, having no diagnosed diseases, thus serving as a reliable reference. The database offers flexible selection criteria, including demographics, BMI, and lifestyle to tailor the reference group precisely.
This tool significantly advances experimental metabolomics by answering recurring questions about normal metabolite concentration ranges, ultimately strengthening research with solid data and broadening our understanding of metabolic processes. Collaborations within the scientific community provide further empowerment as insights are gathered and shared.

