Estibaliz Gómez de Mariscal
Machine-Learning Guided Microscopy
Started on October, 2021
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Overview: I'm interested in understanding cell-level biology using bioimage analysis. My research centers on facing the challenges when applying machine-learning techniques to microscopy images and on contributing to biological discoveries with it. Previously, I developed methods to process TEM images and phase-contrast time-lapse movies to contribute to the characterization of cancer cell motility. I have also conceived new biostatistical approaches to analyse big data. I'm also one of the creators of deepImageJ, an environment to bridge deep-learning to ImageJ. A crucial part of my work and dedication is to make computational tools accessible (open and user-friendly) and reusable, and train non-experts to benefit from them. As a postdoc in Ridardo's lab I'll be learning (a lot) of super-resolution microscopy, and building novel machine-learning methodologies applied to it.
Research themes with our lab
Resources
Collaborators
Florian Jug
Guillaume Jacquemet
Isabel Llorente-García
Mike Heilemann
Mariana Pinho
Martin Weigert
Seamus Holden
Uwe Schmidt
Publications with our group (see more on Google Scholar)
| 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 Published in Nature Communications Biology, July 2022 (see publication) |
| 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 Published in bioRxiv, June 2022 (see preprint) |