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)
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. 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 : 10.1109/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
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. 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
