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Lior Ben Shabat

ORCID: 0009-0005-4606-7045
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About
Contact & Profiles
A5092859047
Research Areas
  • Cell Image Analysis Techniques
  • Single-cell and spatial transcriptomics
  • Advanced Fluorescence Microscopy Techniques
  • AI in cancer detection

Weizmann Institute of Science
 2023-2025

 High-dimensional imaging using combinatorial channel multiplexing and deep learning
OPENALEX - Publications 
Raz Ben-Uri Lior Ben Shabat Dana Shainshein Omer Bar-Tal Yuval Bussi and 11 more Noa Maimon Tal Keidar Haran Idan Milo Inna Goliand Yoseph Addadi Tomer‐Meir Salame Alexander Rochwarger Christian M. Schürch Shai Bagon Ofer Elhanani Leeat Keren

10.1038/s41587-025-02585-0 article EN Nature Biotechnology 2025-03-25
 Escalating High-dimensional Imaging using Combinatorial Channel Multiplexing and Deep Learning
OPENALEX - Publications 
Raz Ben-Uri Lior Ben Shabat Dana Shainshein Omer Bar-Tal Yuval Bussi and 11 more Noa Maimon Tal Keidar Haran Idan Milo Inna Goliand Yoseph Addadi Tomer‐Meir Salame Alexander Rochwarger Christian M. Schürch Shai Bagon Ofer Elhanani Leeat Keren

Abstract Understanding tissue structure and function requires tools that quantify the expression of multiple proteins at single-cell resolution while preserving spatial information. Current imaging technologies use a separate channel for each individual protein, inherently limiting their throughput scalability. Here, we present CombPlex (COMBinatorial multiPLEXing), combinatorial staining platform coupled with an algorithmic framework to exponentially increase number can be measured from C...

10.1101/2023.09.09.556962 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-09-12
 Escalating High-dimensional Imaging using Combinatorial Channel Multiplexing and Deep Learning
OPENALEX - Publications 
Leeat Keren Raz Ben-Uri Lior Ben Shabat Omer Bar-Tal Yuval Bussi and 7 more Noa Maimon Tal Keidar Haran Idan Milo Ofer Elhanani Alexander Rochwarger Christian M. Schürch Shai Bagon

Abstract Understanding tissue structure and function requires tools that quantify the expression of multiple proteins at single-cell resolution while preserving spatial information. Current imaging technologies use a separate channel for each individual protein, inherently limiting their throughput scalability. Here, we present CombPlex (COMBinatorial multiPLEXing), combinatorial staining platform coupled with an algorithmic framework to exponentially increase number can be measured from C...

10.21203/rs.3.rs-3350576/v1 preprint EN cc-by Research Square (Research Square) 2024-02-28
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