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Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data

Research Bioinformatics AI

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TL;DR - Spatialproteomics is a Python toolbox for end-to-end analysis of highly multiplexed fluorescence imaging data. Its emphasis on interoperability could help standardize spatial proteomics workflows.

  • Published online in Nature Methods on 24 July 2026.
  • Supports analysis across the full multiplexed imaging workflow.
  • Designed specifically for highly multiplexed fluorescence image data.
  • The provided content does not describe algorithms, benchmarks, or biological findings.

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Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data

Nature Methods Matthias Meyer-Bender, Harald Vöhringer, Christina Schniederjohann, Sarah Koziel, Erin Chung, Ekaterina Popova, Alexander Brobeil, Nicklas Griese, Nora Kolks, Lisa-Maria Held, Aamir Munir, Mikaela Koutrouli, Luca Marconato, Wouter-Michiel Vierdag, Lucas Diedrich, Vincenth Brennsteiner, Theodoros Visvikis, Jose Nimo, Panos Roussos, Erwin Schoof, Sascha Dietrich, Peter-Martin Bruch, Wolfgang Huber 2026-07-24 doi:10.1038/s41592-026-03155-1

TL;DR - Spatialproteomics is a Python toolbox for end-to-end analysis of highly multiplexed fluorescence imaging data. Its emphasis on interoperability could help standardize spatial proteomics workflows.

  • Published online in Nature Methods on 24 July 2026.
  • Supports analysis across the full multiplexed imaging workflow.
  • Designed specifically for highly multiplexed fluorescence image data.
  • The provided content does not describe algorithms, benchmarks, or biological findings.
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