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Dataset . 2023
License: CC BY
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Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
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Benchmark FIB SEM and Airyscan data of HeLa cells

Research datakeyboard_double_arrow_right Dataset 15 May 2023 English Publisher:Zenodo
Authors: Krentzel, Daniel; Elphick, Matouš; Domart, Marie-Charlotte; Peddie, Christopher J.; Laine, Romain F.; Henriques, Ricardo; Collinson, Lucy M.; +1 Authors

doi: 10.5281/zenodo.7936982 , 10.5281/zenodo.7936981

Benchmark FIB SEM and Airyscan data of HeLa cells

Abstract

This work was supported by The Francis Crick Institute which receives its core funding from Cancer Research UK (CC001999), the UK Medical Research Council (CC001999), and the Wellcome Trust (CC001999). D.K. was funded by The Francis Crick Institute and the Pasteur-Paris University International doctoral program (PPU). R.F.L. was supported by a Medical Research Council Skills development fellowship (MR/T027924/1). R.H. is supported by the Gulbenkian Foundation (Fundação Calouste Gulbenkian) and received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement number 101001332), the European Molecular Biology Organization (EMBO) Installation Grant (EMBO-2020-IG4734) and the Chan Zuckerberg Initiative Visual Proteomics Grant (vpi-0000000044). Matt Russell (Electron Microscopy Science Technology Platform, The Francis Crick Institute and Centre for Ultrastructural Imaging, King's College London) collected preliminary CLEM data used in testing.

Sample volume electron microscopy dataset cropped from EMPIAR-10819 and fluorescence dataset from BioImage Archive S-BSST707 for the CLEM-Reg paper.

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Keywords

electron microscopy, deep learning, alignment, fluorescence microscopy

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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