Gómez-de-Mariscal Lab about
Estibaliz Gómez-de-Mariscal
Group Leader
AI and Microscopy for Biomedical Discovery
Our group works at the interface of AI, microscopy and biology to understand how cellular organisation and dynamics govern function in health and disease across multiple levels of complexity.
Our research combines machine learning, bioimage analysis, microscopy and cell biology to extract quantitative, high-dimensional information from complex imaging data. By integrating multidisciplinary computational and experimental approaches, we aim to uncover how cells adapt to and interact with their microenvironment across multiple spatial and temporal scales.
We collaborate closely with researchers across diverse disease areas, including cancer, viral infection and neurodegenerative diseases, using both in vitro and in vivo models. These collaborations allow us to address biological questions across scales, from controlled experimental systems to clinically relevant contexts.
Alongside our research, we develop open, accessible and reproducible tools that enable the broader community to analyse and interpret biological imaging data. Ultimately, our goal is to develop transformative methodologies to support a more quantitative, predictive and integrative approach to biomedical discovery.
In the lab, we are committed to fostering an inclusive and collaborative scientific environment that encourages creativity, diversity and out-of-the-box thinking. We believe that different backgrounds, perspectives and ways of thinking are essential drivers of innovation and discovery.
Gómez-de-Mariscal Lab team
Meet Our Team
Gómez-de-Mariscal Lab Selected Publications
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Hidalgo-Cenalmor I, Pylvänäinen JW, Ferreira MG, Russell CT, Saguy A, Arganda-Carreras I, Shechtman Y, Jacquemet G*, Henriques R*, Gómez de Mariscal E*. DL4MicEverywhere – deep learning for microscopy made flexible, shareable and reproducible. Nature Methods (2024) (doi:10.1038/s41592-024-02295-6)
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Del Rosario M&, Gómez-de-Mariscal E&, Morgado L, Portela R, Pereira PM*, R. Henriques*. PhotoFiTT: A Quantitative Framework for Assessing Phototoxicity in Live-Cell Microscopy Experiments. Nature Communications (2025) (doi: 10.1038/s41467-025-66209-6)
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Ferreira, M.G., Saraiva, B.M., Brito, A.D., Pinho, M.G., Henriques, R.* and Gómez-de-Mariscal, E.* ReScale4DL: Balancing Pixel and Contextual Information for Enhanced Bioimage Segmentation. bioRxiv (2025) (doi:10.1101/2025.04.09.647871)
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Gómez-de-Mariscal E & Grobe H & Pylvänäinen JW, Xénard L, Henriques R, Tinevez JY, Jacquemet G. CellTracksColab – A platform for compiling, analyzing, and exploring tracking data. PLOS Biology (2024) (doi:10.1371/journal.pbio.3002740)
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Gómez-de-Mariscal E & Garcı́a-López-de-Haro C , Ouyang W, and Donati L, Lundberg E, Unser M, Muñoz-Barrutia A*, Sage D*. DeepImageJ: A user-friendly environment to run deep learning models in ImageJ. Nature Methods (2021) (doi:10.1038/s41592-021-01262-9)
