Real-Time high-content Super-Resolution Imaging of ES Cell States
Alias: RT-SuperES
Agency: H2022
Type: EIC Pathfinder Open
Principal Investigator: Eran Meshorer
Investigators: Eran Meshorer, Ricardo Henriques, Anna Kreshuk, Sandrine Lévêque-Fort, Nicolas Bourg, Genevieve Almouzni
Start-date: April 2022
End-date: March 2027
DOI: 10.3030/101099654
Agency: H2022
Type: EIC Pathfinder Open
Principal Investigator: Eran Meshorer
Investigators: Eran Meshorer, Ricardo Henriques, Anna Kreshuk, Sandrine Lévêque-Fort, Nicolas Bourg, Genevieve Almouzni
Start-date: April 2022
End-date: March 2027
DOI: 10.3030/101099654
RT-SuperES is a project that creates a novel microscope equipped with machine learning-based automated decision making, allowing high-content imaging of embryonic stem cells in real-time. By combining conventional and super-resolution imaging, it explores cellular processes during differentiation at a nanoscale level. It will use cutting-edge technologies such as SNAP-tagging, SRRF, SMLM, SIM, NanoJ-Fluidics, and AI algorithms. The project brings together a multidisciplinary team across four countries to establish this groundbreaking and affordable imaging technology.
Technology explored
Supported publications
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Harnessing artificial intelligence to reduce phototoxicity in live imaging Estibaliz Gómez-de-Mariscal, Mario Del Rosario, Joanna W. Pylvänäinen, Guillaume Jacquemet, Ricardo Henriques Perspective published in Journal of Cell Science, February 2024 Technologies: BioImage Model Zoo, CARE, DeepBacs, NanoJ-SRRF and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1242/jcs.261545 |
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The Rise of Data-Driven Microscopy powered by Machine Learning Leonor Morgado, Estibaliz Gómez-de-Mariscal, Hannah S Heil, Ricardo Henriques Preprint published in arXiv, January 2024 Technologies: BioImage Model Zoo, DL4MicEverywhere, NanoJ, NanoJ-Fluidics and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC, FCT, H2021 and H2022 DOI: 10.48550/arXiv.2401.05282 |
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DL4MicEverywhere - Deep learning for microscopy made flexible, shareable, and reproducible Iván Hidalgo-Cenalmor, Joanna W Pylvänäinen, Mariana G Ferreira, Craig T Russell, Ignacio Arganda-Carreras, AI4Life Consortium, Guillaume Jacquemet, Ricardo Henriques, Estibaliz Gómez-de-Mariscal Preprint published in bioRxiv, November 2023 Technologies: BioImage Model Zoo, DeepBacs, DL4MicEverywhere and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1101/2023.11.19.567606 |
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High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation Romain F. Laine, Hannah S. Heil, Simao Coelho, Jonathon Nixon-Abell, Angélique Jimenez, Theresa Wiesner, Damián Martínez, Tommaso Galgani, Louise Régnier, Aki Stubb, Gautier Follain, Samantha Webster, Jesse Goyette, Aurelien Dauphin, Audrey Salles, Siân Culley, Guillaume Jacquemet, Bassam Hajj, Christophe Leterrier, Ricardo Henriques Paper published in Nature Methods, November 2023 Technologies: CARE, NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoPyx and Nuclear-Pores as references Funded by: CZI, EMBO, ERC, FCT, H2021, H2022, InnOValley and Wellcome Trust News: Photonics.com, The Science Times, Optics.org and Phys.org Blogs: Springer Nature Protocols and Methods Community DOI: 10.1038/s41592-023-02057-w |
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Transertion and cell geometry organize the Escherichia coli nucleoid during rapid growth Christoph Spahn, Stuart Middlemiss, Estibaliz Gómez-de-Mariscal, Ricardo Henriques, Helge B. Bode, Séamus Holden, Mike Heilemann Preprint published in bioRxiv, October 2023 Technologies: CARE, DeepBacs and ZeroCostDL4Mic Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1101/2023.10.16.562172 |
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NanoPyx - super-fast bioimage analysis powered by adaptive machine learning Bruno M. Saraiva, Inês M. Cunha, António D. Brito, Gautier Follain, Raquel Portela, Robert Haase, Pedro M. Pereira, Guillaume Jacquemet, Ricardo Henriques Preprint published in bioRxiv, August 2023 Technologies: CARE, NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoJ-VirusMapper and NanoPyx Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1101/2023.08.13.553080 |
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