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Updated: Sep 8, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

MetaboSERV-a platform for selecting, exchanging, and visualizing metabolomics data with controlled data access.

Tim Tucholski¹, Angela Maennel², Yacoub Abelard Njipouombe Nsangou^1,3

¹Department of Medical Bioinformatics, University Medical Center Göttingen, 37077 Göttingen, Germany.

|August 1, 2025

Summary

This summary is machine-generated.

MetaboSERV is a new platform for sharing quantitative metabolomics data securely. It enables researchers to integrate, visualize, and compare datasets while preserving privacy for collaborative research.

Keywords:

(privacy-preserving) data sharing collaborative research mass spectrometry metabolomics nuclear magnetic resonance spectroscopy

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Area of Science:

Metabolomics
Bioinformatics
Data Science

Background:

Increasing number of metabolomics studies utilize high-dimensional data from mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy.
Existing public metabolomics data repositories offer limited privacy-preserving data sharing options.
Need for secure platforms for sharing and analyzing complex metabolomics data.

Purpose of the Study:

To introduce MetaboSERV, an open-source platform for managing and sharing quantitative metabolomics data.
To facilitate data selection, integration, and controlled access for researchers.
To support privacy-preserving data sharing for collaborative and interdisciplinary research.

Main Methods:

Development of a browser-based platform with controlled data access functionalities.
Implementation of features for data browsing, visualization, and cross-dataset comparison.
Design for extensibility and adaptability with self-managed instances using Docker images.

Main Results:

MetaboSERV provides a secure environment for sharing quantitative metabolomics data and metadata.
The platform enables researchers to analyze and compare data across different datasets.
Offers controlled access functionalities to ensure privacy-preserving data sharing.

Conclusions:

MetaboSERV is available as an open-source, browser-based platform for metabolomics data management.
The platform supports collaborative research through secure and privacy-preserving data sharing.
Source code and configurable Docker images are provided for self-managed instances.