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Auguste Genovesio

Computational Bioimaging
and Bioinformatics

This team is part of the Computational Biology Center.

The research project of our team is the study of cellular morphology and dynamics at large scale. We are interested in characterizing the morphological heterogeneity of cellular responses to perturbations. We thus work to identify mechanical or molecular factors of cell morphology, organization and activity in different contexts. In this perspective, on one hand we contribute to generate large data sets of images or gene expression. On the other hand, we interpret these large data sets to produce and validate predictive models. As the scale of the data produced this way constrains us to full automation and quantitative approaches, we develop algorithms and tools for the analysis of large image data. The members of our team bring together a wide range of expertise such as machine and deep learning, computer science, applied mathematics, biophysics and genomic analysis. We apply our approaches to scientific questions we raise such as understanding the action of small compounds with the support of our collaborators from the Curie Institute next door and the pharmaceutical industry. We also develop approaches dedicated to fundamental biology research through a strong interaction with our colleagues at IBENS, Collège de France and ESPCI in various subfields such as functional genomics, developmental biology and neuroscience.

Recent selected publications

(Full list of publications and patents available here )

Reconstructing Interpretable Features in Computational Super-Resolution microscopy via Regularized Latent Search
M. Gheizari, and A. Genovesio
2024, Biological Imaging doi: doi:10.1017/S2633903X24000084

ChAda-ViT : Channel Adaptive Attention for Joint Representation Learning of Heterogeneous Microscopy Images
N. Bourriez*, I. Bendidi*, E. Cohen*, G. Watkinson, M. Sanchez, G. Bollot, A. Genovesio
2024, CVPR doi: 10.48550/arXiv.2311.15264

Weakly supervised cross-modal learning in high-content screening
G. Watkinson*, E. Cohen*, N. Bourriez, I. Bendidi, G. Bollot, A. Genovesio
2024, IEEE ISBI doi: 10.48550/arXiv.2311.04678

One Style is All you Need to Generate a Video
S. Manandhar, A. Genovesio

Transfer learning for versatile and training free high content screening analyses
M. Corbe, G. Boncompain, F. Perez, E. Del Nery & A. Genovesio
2023, Scientific Reports, doi: 10.1038/s41598-023-49554-8

No Free Lunch in Self Supervised Representation Learning
I. Bendidi, A. Bardes, E. Cohen, A. Lamiable, G. Bollot, A. Genovesio
2023, NeurIPS, Self-Supervised Learning - Theory and Practice

Revealing invisible cell phenotypes with conditional generative modeling
A. Lamiable*, T. Champetier*, F. Leonardi, E. Cohen, P. Sommer, D. Hardy, N. Argy, A. Massougbodji, E. Del Nery, G. Cottrell, Y.-J. Kwon, A. Genovesio
2023, Nature communications, doi: 10.1038/s41467-023-42124-6

Cell painting transfer increases screening hit rate
E. Cohen, M. Corbe, C. A. Franco, F. F. Vasconcelos, F. Perez, E. Del Nery, G. Bollot and A. Genovesio
2023, Biological Imaging, doi: 10.1017/S2633903X23000077

Evolution is not uniform along coding sequences
R. Bricout, D. Weil, D. Stroebel, A. Genovesio, H. Roest Crollius
2023, Molecular Biology and Evolution, doi: 10.1093/molbev/msad042

Super-Resolution through StyleGAN Regularized Latent Search
M. Gheizari, and A. Genovesio
2022, NeurIPS, Self-Supervised Learning - Theory and Practice

Unpaired Image-to-Image Translation with Limited Data to Reveal Subtle Phenotypes
A. Bourou, K. Daupin, V. Dubreuil, A. De Thonel, V. Lallemand-Mezger, and A. Genovesio
2022, NeurIPS, Self-Supervised Learning - Theory and Practice

Comparison of semi-supervised learning methods for High Content Screening quality control
U. Masud∗, E. Cohen∗, I. Bendidi, G. Bollot, and A. Genovesio
2022, ECCV, doi: 10.1007/978-3-031-25069-9_26

SAVGAN: Self-Attention based Generation of Tumour on Chip videos
S. Manandhar, I. Veith, M.-C. Parrini, A. Genovesio
2022, IEEE ISBI, pp. 1-5, doi: 10.1109/ISBI52829.2022.9761518

Non-convex cell epithelial modeling unveils cellular interactions
E. Laruelle and A. Genovesio
2022, IEEE ISBI, pp. 1-5, doi: 10.1109/ISBI52829.2022.9761452

Objective Comparison of High Throughput qPCR Data Analysis Methods
M. Bahin, M. Delagrange, Q. Viautour, J. Pouch, A. Ali Chaouche, B. Ducos and A. Genovesio
2021, J Appl Bioinformat Computat Biol S Vol: 10 Issue: 4

Unraveling spatial cellular pattern by computational tissue shuffling
E. Laruelle, N. Spassky, A. Genovesio
2020, Communications Biology

In vivo large-scale analysis of Drosophila neuronal calcium traces by automated tracking of single somata
F Delestro*, L Scheunemann*, M Pedrezzani, P Tchenio, T Preat, A Genovesio
2020, Scientific Reports

Active Fluctuations of the Nuclear Envelope Shape the Transcriptional Dynamics in Oocytes
M Almonacid, A Al Jord, S El-Hayek, A Othmani, F Coulpier, S Lemoine, K Miyamoto, R Grosse, C Klein, T Piolot, P Mailly, R Voituriez, A Genovesio, M-H Verlhac
2019, Developmental Cell

PySpacell: A Python Package for Spatial Analysis of Cell Images.
F Rose, L Rappez, SH Triana, T Alexandrov, A Genovesio
2019, Cytometry Part A

ALFA: annotation landscape for aligned reads
M Bahin*, B F Noel*, V Murigneux, C Bernard, L Bastianelli, H Le Hir, A Lebreton, A Genovesio
2019, BMC Genomics

Monitored eCLIP: high accuracy mapping of RNA-protein interactions
R Hocq*, J Paternina*, Q Alasseur, A Genovesio, H Le Hir
2018, Nucleic Acid Research

High‐Throughput Optical Mapping of Replicating DNA
F De Carli*, N Menezes*, W Berrabah, V Barbe, A Genovesio, O Hyrien
2018, Small Methods

Smooth 2D manifold extraction from 3D image stack
A Shihavuddin*, S Basu*, E Rexhepaj, F Delestro, N Menezes, SM Sigoillot, E Del Nery, F Selimi, N Spassky, A Genovesio
2017, Nature Communications

Compound Functional Prediction Using Multiple Unrelated Morphological Profiling Assays
F Rose*, S Basu*, E Rexhepaj, A Chauchereau, E Del Nery, A Genovesio
2017, SLAS Technology

Detection and tracking of overlapping cell nuclei for large scale mitosis analyses
Y Li*, F Rose*, F di Pietro, X Morin, A Genovesio
2016, BMC bioinformatics