Auguste Genovesio
🇫🇷
Bio-imagerie Computationnelle
et Bioinformatique
Cette Ă©quipe fait partie du Centre de Biologie Computationnelle.
Le projet de recherche de notre Ă©quipe est lâĂ©tude de la morphologie et de la dynamique cellulaires Ă grande Ă©chelle. Nous nous intĂ©ressons notamment Ă caractĂ©riser lâhĂ©tĂ©rogĂ©nĂ©itĂ© morphologique des rĂ©ponses cellulaires aux perturbations. Nous travaillons Ă©galement Ă lâidentification de facteurs mĂ©caniques ou molĂ©culaires de la morphologie, de lâorganisation et de lâactivitĂ© cellulaires. Dans cette optique, nous tentons dâune part de gĂ©nĂ©rer de nouvelles sources dâinformations Ă grande Ă©chelle telles que de larges jeux dâimages ou dâexpression gĂ©nique. Dâautre part, nous interprĂ©tons ces grandes donnĂ©es pour produire et valider des modĂšles prĂ©dictifs. Parce que lâĂ©chelle des donnĂ©es ainsi produites nous contraint Ă des approches exclusivement automatisĂ©es et quantitatives, nous mettons au point des algorithmes et des outils dâanalyse de grandes donnĂ©es dâimages et NGS. Les membres de notre Ă©quipe regroupent un panel de compĂ©tences variĂ©es telles que lâapprentissage automatique et profond, l’informatique, les mathĂ©matiques appliquĂ©es, la biophysique et lâanalyse gĂ©nomique. Nous appliquons nos approches Ă des questions dĂ©veloppĂ©es de maniĂšre autonome comme la comprĂ©hension de lâaction de composĂ©s Ă visĂ©e thĂ©rapeutique avec le concours de nos collaborateurs de lâInstitut Curie et de lâindustrie pharmaceutique. Nous les appliquons Ă©galement Ă des questions de biologie fondamentale grĂące Ă une interaction forte avec nos collaborateurs de lâIBENS, du CollĂšge de France et de lâESPCI : notamment en gĂ©nomique fonctionnelle, en biologie du dĂ©veloppement ou en neuroscience.
Sélection de publications récentes
(Liste complete des publications et brevets ici)
Large Scale Cell Painting Guided Compound Selection Reveals Activity Cliffs and Functional Relationships
M. Sanchez, N. Bourriez, I. Bendidi, E. Cohen, I. Svatko, E. Del Nery, H. Tajmouati, G. Bollot, L. Calzone✉, A. Genovesio✉
2026, Communications Biology, doi : 10.1038/s42003-025-09500-y
DiViD : Disentangled Video Diffusion for StaticâDynamic Factorization
M. Gheisari, and A. Genovesio✉
2025, ICCV DRL4Real
A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features
I. Bendidi, Y. El Mesbahi, A. Kaye Denton, K. Suri, K. Kenyon-Dean, A. Genovesio✉, E. Noutahi✉
2025, ICML
Revealing Subtle Phenotypes in Small Microscopy Datasets Using Latent Diffusion Models
A. Bourou*, B. Castaño Segade*, T. Boyer, V. Mezger, A. Genovesio✉
2025, CVPR CVDD, doi : 10.48550/arXiv.2502.09665
In vivo autofluorescence lifetime imaging of the Drosophila brain captures metabolic shifts associated with memory formation
P. Roussel, M. Zhou, C. Stringari, T. Preat, P.-Y. Plaçais✉, A. Genovesio✉
2025, eLife, doi : 10.7554/eLife.106040.1
Exploring self-supervised learning biases for microscopy image representation
I. Bendidi, A. Bardes, E. Cohen, A. Lamiable, G. Bollot, A. Genovesio✉
2024, Biological Imaging, doi:10.1017/S2633903X2400014X
PhenDiff : Revealing Invisible Phenotypes with Conditional Diffusion Models in Real Images
A. Bourou*, T. Boyer*, M. Gheisari, K. Daupin, V. Dubreuil, A. De Thonel, V. Mezger, A. Genovesio✉
2024, MICCAI doi : 10.1007/978-3-031-72384-1_34
Reconstructing Interpretable Features in Computational Super-Resolution microscopy via Regularized Latent Search
M. Gheisari, 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 : 10.1109/CVPR52733.2024.01098
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 : 10.1109/ISBI56570.2024.10635200
One Style is All you Need to Generate a Video
S. Manandhar, A. Genovesio✉
2024, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 5038-5047, doi : 10.1109/wacv57701.2024.00496
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. Gheisari, 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. Masudâ, E. Cohenâ, 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,
2018, Nucleic Acid Research
HighâThroughput Optical Mapping of Replicating DNA
F De Carli*, N Menezes*, W Berrabah, V Barbe,
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,
2017, Nature Communications
Compound Functional Prediction Using Multiple Unrelated Morphological Profiling Assays
F Rose*, S Basu*, E Rexhepaj, A Chauchereau, E Del Nery,
2017, SLAS Technology
Detection and tracking of overlapping cell nuclei for large scale mitosis analyses
Y Li*, F Rose*, F di Pietro, X Morin,
2016, BMC bioinformatics
