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Updated: Jun 12, 2026

Exploring the Effects of Spaceflight on Mouse Physiology using the Open Access NASA GeneLab Platform
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A Step-by-Step Protocol From METASPACE to Biological Interpretation.

Abigail Moreno-Pedraza1, Brittney Gorman1, Marija Velickovic1

  • 1Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.

Journal of Mass Spectrometry : JMS
|June 11, 2026
PubMed
Summary
This summary is machine-generated.

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This tutorial introduces an R-pipeline to analyze mass spectrometry imaging (MSI) data using the METASPACE platform. It helps researchers extract biological insights from complex untargeted metabolomic datasets.

Area of Science:

  • Molecular imaging
  • Metabolomics
  • Bioinformatics

Background:

  • Mass spectrometry imaging (MSI) offers spatial molecular analysis of biological systems.
  • Large MSI datasets pose challenges for extracting biological insights.
  • The METASPACE platform facilitates MSI data processing and interpretation using machine learning.

Purpose of the Study:

  • To present a user-friendly R-pipeline for METASPACE users.
  • To guide the navigation of untargeted metabolomic annotations.
  • To translate MSI data into practical biological insights for complex systems.

Main Methods:

  • Development of a detailed R-pipeline.
  • Leveraging the METASPACE cloud-based platform.
  • Focus on untargeted metabolomic annotation within MSI data.

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Main Results:

  • The pipeline simplifies the analysis of complex MSI datasets.
  • Facilitates the translation of molecular data into biological understanding.
  • Demonstrates a practical approach for MSI data interpretation.

Conclusions:

  • The R-pipeline enhances the utility of METASPACE for MSI data analysis.
  • This approach supports diagnostics, drug discovery, and environmental research.
  • The pipeline is valuable for both new and experienced MSI researchers.