Programme
| Heures |
événement |
|
|
09:30 - 09:45
|
Introduction |
|
|
09:45 - 11:00
|
Deep Learning for Structural Data |
|
|
09:45 - 10:30 |
› Rationalizing machine learning on biomolecules structures, applications to RNA therapeutics and PPI predictions - Vincent Mallet, Centre de Bioinformatique |
|
|
10:30 - 11:00 |
› DLScaff: Deep Learning for Hi-C Assembly Correction and Scaffolding - Alexis Mergez, Unité de Mathématiques et Informatique Appliquées de Toulouse |
|
|
11:00 - 11:30
|
Pause café |
|
|
11:30 - 12:30
|
Interpretability and Transfer Learning in Transcriptomics |
|
|
11:30 - 12:00 |
› A Biologically Interpretable Approach To Identify New Therapeutics Targets Using Deep Neural Networks - Charlotte Job, Informatique, BioInformatique, Systèmes Complexes |
|
|
12:00 - 12:30 |
› Adversarial Domain Adaptation Enables Knowledge Transfer Across RNA-Seq Datasets - Kevin DRADJAT, Informatique, BioInformatique, Systèmes Complexes (IBISC) |
|
|
12:30 - 14:15
|
Déjeuner + Poster session |
|
|
14:15 - 15:30
|
Phylogenetics and Phylodynamics |
|
|
14:15 - 15:00 |
› Estimating factors of epidemic spread with deep learning-enabled phylodynamics - Anna Zhukova, Institut de biologie de l'ENS Paris, Institut Pasteur |
|
|
15:00 - 15:30 |
› Graph Neural Networks for Likelihood-Free Inference in Diversification Models - Amélie Leroy, Biologie Computationnelle, Quantitative et Synthétique, Modélisation de la Biologie |
|
|
15:30 - 16:00
|
Pause café |
|
|
16:00 - 16:30
|
Phylogenetics and Phylodynamics |
|
|
16:00 - 16:30 |
› Likelihood-free inference of phylogenetic tree posterior distributions - Luc Blassel, Biologie Computationnelle, Quantitative et Synthétique [Paris] (ex LCQB) |
|
|
16:30 - 17:00
|
Representation Learning in (Epi)genomics |
|
|
16:30 - 17:00 |
› Spreading of methylation of transposable elements in A.Thaliana - Ekaterina Antonenko, CBIO-Centre for Computational Biology, U1331, Institut Curie, PSL-Research University |
|
|
17:00 - 17:30
|
Closing remarks |
|
vendredi 28 novembre 2025
| Heures |
événement |
|
|
09:00 - 09:10
|
Introduction - Raphael Mourad |
|
|
09:10 - 10:00
|
LLM en métagénomique - Jean-Daniel Zucker |
|
|
10:00 - 10:20
|
CRE en génomique des plantes - Marie-Laure Martin and Sylvie Coursol |
|
|
10:20 - 10:40
|
Deep learning pour la génomique des plantes - Mikael Lucas |
|
|
10:20 - 11:40
|
Deep learning pour la génomique des animaux d’élevages - Raphaël Mourad |
|
|
10:40 - 11:00
|
Pause café |
|
|
11:00 - 11:20
|
Retour sur Evo2 - Guillaume Gautreau |
|
|
11:40 - 12:00
|
Modèle fondation multiéchelles - Jérémie Kalfon |
|
|
12:00 - 12:20
|
Deep learning pour le génome 3D - Thomas Faraut |
|
|
12:30 - 13:30
|
Déjeuner |
|
|
Chargement... 
