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Related Concept Videos

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...

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Related Experiment Video

Updated: Jun 21, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
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TraceMetrix: a traceable metabolomics interactive analysis platform.

Wei Chen1, Yanpeng An2, Ziru Chen3

  • 1Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.

Journal of Cheminformatics
|September 30, 2025
PubMed
Summary
This summary is machine-generated.

TraceMetrix enhances metabolomics research by providing interactive traceability for data analysis. This web-based platform improves reproducibility by tracking data, software, and parameters throughout the analysis pipeline.

Keywords:
Interactive analysis platformMetabolomicsReproducibilityTraceable

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Metabolomics

Background:

  • Metabolomics data analysis faces challenges with data sharing and transparency, hindering reproducibility.
  • Existing bioinformatics tools offer partial solutions, but simplicity and clarity are needed for full potential realization.

Purpose of the Study:

  • Introduce TraceMetrix, a web-based platform for interactive traceability in metabolomics data analysis.
  • Enhance the reproducibility and operational clarity of metabolomics workflows.

Main Methods:

  • Developed a web-based platform (TraceMetrix) for flexible data management and tracking.
  • Documented software and parameters across four analysis modules: preprocessing, cleaning, statistical, and functional analysis.
  • Mapped upstream/downstream relationships for 19 analytical functions, ensuring end-to-end traceability.

Main Results:

  • Demonstrated TraceMetrix's traceability function using a non-targeted metabolomics dataset.
  • Successfully optimized parameter selection and reproduced analysis processes.
  • Validated original study findings, confirming the platform's effectiveness.

Conclusions:

  • TraceMetrix integrates data, software, and process traceability, significantly improving reproducibility in metabolomics.
  • The platform supports diverse applications and is available for free use.
  • Facilitates efficient batch processing of large-scale datasets via a high-performance computing cluster.