Research Team


Guillaume Jacquemet

Guillaume Jacquemet

Group Leader

Abo Akademi University, Turku, Finland

Guillaume Jacquemet is a group leader at the Turku Bioscience Centre, University of Turku, Finland. His research focuses on the molecular mechanisms of cell adhesion and migration in health and disease. He is particularly interested in the role of the extracellular matrix in cancer progression and metastasis. His lab uses a combination of cell biology, biochemistry, biophysics and advanced microscopy techniques to study the molecular mechanisms of cell adhesion and migration in health and disease.


Publications with our group (see more on Google Scholar):


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
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
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
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
Live-cell imaging in the deep learning era
Joanna W Pylvänäinen, Estibaliz Gómez-de-Mariscal, Ricardo Henriques, Guillaume Jacquemet
Review published in Current Opinion in Cell Biology, January 2023
Technologies: BioImage Model Zoo, CARE, DeepBacs, Fast4DReg, NanoJ, NanoJ-eSRRF, NanoJ-Fluidics, NanoJ-SRRF and ZeroCostDL4Mic
Funded by: CZI, EMBO, ERC and H2021
DOI: 10.1016/j.ceb.2023.102271
Fast4DReg–fast registration of 4D microscopy datasets
Joanna W Pylvänäinen, Romain F Laine, Bruno MS Saraiva, Sujan Ghimire, Gautier Follain, Ricardo Henriques, Guillaume Jacquemet
Paper published in Journal of Cell Science, January 2023
Technologies: CARE, Fast4DReg, NanoJ and ZeroCostDL4Mic
Funded by: CZI and ERC
DOI: 10.1242/jcs.260728
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian, Michael Hecht, Artur Yakimovich, Kristina Monakhova, Laura Waller, Ivo F Sbalzarini, Christopher A Metzler, Mingyang Xie, Kevin Zhang, Isaac CD Lenton, Halina Rubinsztein-Dunlop, Daniel Brunner, Bijie Bai, Aydogan Ozcan, Daniel Midtvedt, Hao Wang, Nataša Sladoje, Joakim Lindblad, Jason T Smith, Marien Ochoa, Margarida Barroso, Xavier Intes, Tong Qiu, Li-Yu Yu, Sixian You, Yongtao Liu, Maxim A Ziatdinov, Sergei V Kalinin, Arlo Sheridan, Uri Manor, Elias Nehme, Ofri Goldenberg, Yoav Shechtman, Henrik K Moberg, Christoph Langhammer, Barbora Špačková, Saga Helgadottir, Benjamin Midtvedt, Aykut Argun, Tobias Thalheim, Frank Cichos, Stefano Bo, Lars Hubatsch, Jesus Pineda, Carlo Manzo, Harshith Bachimanchi, Erik Selander, Antoni Homs-Corbera, Martin Fränzl, Kevin de Haan, Yair Rivenson, Zofia Korczak, Caroline Beck Adiels, Mite Mijalkov, Dániel Veréb, Yu-Wei Chang, Joana B Pereira, Damian Matuszewski, Gustaf Kylberg, Ida-Maria Sintorn, Juan C Caicedo, Beth A Cimini, Muyinatu A Lediju Bell, Bruno M Saraiva, Guillaume Jacquemet, Ricardo Henriques, Wei Ouyang, Trang Le, Estibaliz Gómez-de-Mariscal, Daniel Sage, Arrate Muñoz-Barrutia, Ebba Josefson Lindqvist, Johanna Bergman
Preprint published in arXiv, January 2023
Technologies: BioImage Model Zoo, CARE and ZeroCostDL4Mic
Funded by: CZI, EMBO, ERC and H2021
DOI: 10.48550/arXiv.2303.03793
DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches
Christoph Spahn, Estibaliz Gómez-de-Mariscal, Romain F. Laine, Pedro M. Pereira, Lucas von Chamier, Mia Conduit, Mariana G. Pinho, Guillaume Jacquemet, Séamus Holden, Mike Heilemann, Ricardo Henriques
Paper published in Communications Biology, July 2022
Technologies: BioImage Model Zoo, CARE, DeepBacs, NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and ZeroCostDL4Mic
Funded by: CZI, ERC and Wellcome Trust
DOI: 10.1038/s42003-022-03634-z
Bioimage model zoo - a community-driven resource for accessible deep learning in bioimage analysis
Wei Ouyang, Fynn Beuttenmueller, Estibaliz Gómez-de-Mariscal, Constantin Pape, Tom Burke, Carlos Garcia-López-de-Haro, Craig Russell, Lucía Moya-Sans, Cristina de-la-Torre-Gutiérrez, Deborah Schmidt, Dominik Kutra, Maksim Novikov, Martin Weigert, Uwe Schmidt, Peter Bankhead, Guillaume Jacquemet, Daniel Sage, Ricardo Henriques, Arrate Muñoz-Barrutia, Emma Lundberg, Florian Jug, Anna Kreshuk
Preprint published in bioRxiv, January 2022
Technologies: BioImage Model Zoo and ZeroCostDL4Mic
Funded by: CZI, EMBO, ERC and H2021
DOI: 10.1101/2022.06.07.495102
Democratising deep learning for microscopy with ZeroCostDL4Mic
Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K. Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L. Jones, Loïc A. Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques
Paper published in Nature Communications, April 2021
Technologies: CARE, FBSR-TFM, NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and ZeroCostDL4Mic
Funded by: EMBO, ERC and Wellcome Trust
News: AZO Life Sciences, Drug Target Review, Nanotechnology Now and The Medical News
Blogs: Microbiome Digest - Bik's Picks
DOI: 10.1038/s41467-021-22518-0
Avoiding a replication crisis in deep-learning-based bioimage analysis
Romain F Laine, Ignacio Arganda-Carreras, Ricardo Henriques, Guillaume Jacquemet
Perspective published in Nature methods, January 2021
Technologies: CARE and ZeroCostDL4Mic
Funded by: EMBO, ERC and Wellcome Trust
DOI: 10.1038/s41592-021-01284-3
The cell biologist's guide to super-resolution microscopy
Guillaume Jacquemet, Alexandre F. Carisey, Hellyeh Hamidi, Ricardo Henriques, Christophe Leterrier
Review published in Journal of Cell Science, June 2020
Technologies: CARE, NanoJ, NanoJ-Fluidics, NanoJ-SRRF, Nuclear-Pores as references and ZeroCostDL4Mic
Funded by: BBSRC and Wellcome Trust
News: ScienMag and EurekAlert!
DOI: 10.1242/jcs.240713
Fluctuation-based super-resolution traction force microscopy
Aki Stubb, Romain F Laine, Mitro Miihkinen, Hellyeh Hamidi, Camilo Guzmán, Ricardo Henriques, Guillaume Jacquemet, Johanna Ivaska
Paper published in Nano letters, January 2020
Technologies: CARE, FBSR-TFM, NanoJ, NanoJ-SQUIRREL and NanoJ-SRRF
Funded by: BBSRC
DOI: 10.1021/acs.nanolett.9b04083