GT LEGO Machine Learning pour la génomique - Automne 2025

Introduction

9:30 - 9:45 (15min)

Introduction

Deep Learning for Structural Data

9:45 - 11:00 (1h15)

Deep Learning for Structural Data

› Rationalizing machine learning on biomolecules structures, applications to RNA therapeutics and PPI predictions - Vincent Mallet, Centre de Bioinformatique 09:45-10:30 (45min)

› DLScaff: Deep Learning for Hi-C Assembly Correction and Scaffolding - Alexis Mergez, Unité de Mathématiques et Informatique Appliquées de Toulouse 10:30-11:00 (30min)

Pause café

11:00 - 11:30 (30min)

Pause café

Interpretability and Transfer Learning in Transcriptomics

11:30 - 12:30 (1h)

Interpretability and Transfer Learning in Transcriptomics

› A Biologically Interpretable Approach To Identify New Therapeutics Targets Using Deep Neural Networks - Charlotte Job, Informatique, BioInformatique, Systèmes Complexes 11:30-12:00 (30min)

› Adversarial Domain Adaptation Enables Knowledge Transfer Across RNA-Seq Datasets - Kevin DRADJAT, Informatique, BioInformatique, Systèmes Complexes (IBISC) 12:00-12:30 (30min)

Déjeuner + Poster session

12:30 - 14:15 (1h45)

Déjeuner + Poster session

Phylogenetics and Phylodynamics

14:15 - 15:30 (1h15)

Phylogenetics and Phylodynamics

› Estimating factors of epidemic spread with deep learning-enabled phylodynamics - Anna Zhukova, Institut de biologie de l'ENS Paris, Institut Pasteur 14:15-15:00 (45min)

› Graph Neural Networks for Likelihood-Free Inference in Diversification Models - Amélie Leroy, Biologie Computationnelle, Quantitative et Synthétique, Modélisation de la Biologie 15:00-15:30 (30min)

Pause café

15:30 - 16:00 (30min)

Pause café

Phylogenetics and Phylodynamics

16:00 - 16:30 (30min)

Phylogenetics and Phylodynamics

› Likelihood-free inference of phylogenetic tree posterior distributions - Luc Blassel, Biologie Computationnelle, Quantitative et Synthétique [Paris] (ex LCQB) 16:00-16:30 (30min)

Representation Learning in (Epi)genomics

16:30 - 17:00 (30min)

Representation Learning in (Epi)genomics

› Spreading of methylation of transposable elements in A.Thaliana - Ekaterina Antonenko, CBIO-Centre for Computational Biology, U1331, Institut Curie, PSL-Research University 16:30-17:00 (30min)

Closing remarks

17:00 - 17:30 (30min)

Closing remarks

	Jeu. 27	Ven. 28
09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00	Introduction 9:30 - 9:45 (15min) Introduction Deep Learning for Structural Data 9:45 - 11:00 (1h15) Deep Learning for Structural Data › Rationalizing machine learning on biomolecules structures, applications to RNA therapeutics and PPI predictions - Vincent Mallet, Centre de Bioinformatique 09:45-10:30 (45min) › DLScaff: Deep Learning for Hi-C Assembly Correction and Scaffolding - Alexis Mergez, Unité de Mathématiques et Informatique Appliquées de Toulouse 10:30-11:00 (30min) Pause café 11:00 - 11:30 (30min) Pause café Interpretability and Transfer Learning in Transcriptomics 11:30 - 12:30 (1h) Interpretability and Transfer Learning in Transcriptomics › A Biologically Interpretable Approach To Identify New Therapeutics Targets Using Deep Neural Networks - Charlotte Job, Informatique, BioInformatique, Systèmes Complexes 11:30-12:00 (30min) › Adversarial Domain Adaptation Enables Knowledge Transfer Across RNA-Seq Datasets - Kevin DRADJAT, Informatique, BioInformatique, Systèmes Complexes (IBISC) 12:00-12:30 (30min) Déjeuner + Poster session 12:30 - 14:15 (1h45) Déjeuner + Poster session Phylogenetics and Phylodynamics 14:15 - 15:30 (1h15) Phylogenetics and Phylodynamics › Estimating factors of epidemic spread with deep learning-enabled phylodynamics - Anna Zhukova, Institut de biologie de l'ENS Paris, Institut Pasteur 14:15-15:00 (45min) › Graph Neural Networks for Likelihood-Free Inference in Diversification Models - Amélie Leroy, Biologie Computationnelle, Quantitative et Synthétique, Modélisation de la Biologie 15:00-15:30 (30min) Pause café 15:30 - 16:00 (30min) Pause café Phylogenetics and Phylodynamics 16:00 - 16:30 (30min) Phylogenetics and Phylodynamics › Likelihood-free inference of phylogenetic tree posterior distributions - Luc Blassel, Biologie Computationnelle, Quantitative et Synthétique [Paris] (ex LCQB) 16:00-16:30 (30min) Representation Learning in (Epi)genomics 16:30 - 17:00 (30min) Representation Learning in (Epi)genomics › Spreading of methylation of transposable elements in A.Thaliana - Ekaterina Antonenko, CBIO-Centre for Computational Biology, U1331, Institut Curie, PSL-Research University 16:30-17:00 (30min) Closing remarks 17:00 - 17:30 (30min) Closing remarks	Introduction 9:00 - 9:10 (10min) Introduction Raphael Mourad LLM en métagénomique 9:10 - 10:00 (50min) LLM en métagénomique Jean-Daniel Zucker CRE en génomique des plantes 10:00 - 10:20 (20min) CRE en génomique des plantes Marie-Laure Martin and Sylvie Coursol Deep learning pour la génomique des plantes Deep learning pour la génomique des animaux d’élevages Pause café Retour sur Evo2 10:20 - 10:40 (20min) Deep learning pour la génomique des plantes Mikael Lucas 10:20 - 11:40 (1h20) Deep learning pour la génomique des animaux d’élevages Raphaël Mourad 10:40 - 11:00 (20min) Pause café 11:00 - 11:20 (20min) Retour sur Evo2 Guillaume Gautreau Modèle fondation multiéchelles 11:40 - 12:00 (20min) Modèle fondation multiéchelles Jérémie Kalfon Deep learning pour le génome 3D 12:00 - 12:20 (20min) Deep learning pour le génome 3D Thomas Faraut Déjeuner 12:30 - 13:30 (1h) Déjeuner