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CellTune: an integrative software for accurate cell classification in spatial proteomics

Research Bioinformatics AI

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TL;DR - CellTune is software for high-precision cell classification in spatial proteomics datasets. It uses human-in-the-loop active learning to integrate expert feedback into the analysis workflow.

  • Targets cell classification in spatial proteomics data.
  • Combines automated analysis with iterative human input.
  • Aims to improve classification accuracy through active learning.
  • The provided abstract does not include quantitative results or benchmarking details.

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CellTune: an integrative software for accurate cell classification in spatial proteomics

Nature Methods Yuval Bussi, Dana Shainshein, Eli Ovits, Sarah Posner, Nofar Azulay, Noa Maimon, Tal Keidar Haran, Raz Ben-Uri, Caitlin Brown, Noam Schuldiner, Eylon Yaniv, David Van Valen, Idan Milo, Ofer Elhanani, Robert Schiemann, Leeat Keren 2026-07-31 doi:10.1038/s41592-026-03162-2
Public signals OpenAlex citations 3
Providers: Hugging Face · N/A OpenAlex · Citations 3 Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-08-30 14:28:45.657775 UTC

TL;DR - CellTune is software for high-precision cell classification in spatial proteomics datasets. It uses human-in-the-loop active learning to integrate expert feedback into the analysis workflow.

  • Targets cell classification in spatial proteomics data.
  • Combines automated analysis with iterative human input.
  • Aims to improve classification accuracy through active learning.
  • The provided abstract does not include quantitative results or benchmarking details.
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