08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
›8:30 (30min)
8:30 - 9:00 (30min)
Breakfast (SCAI)
›9:00 (15min)
9:00 - 9:15 (15min)
Introduction
›9:15 (30min)
9:15 - 9:45 (30min)
Tree-based variational inference for Poisson log-normal models: application to the gut microbiome
Alexandre Chaussard
›9:45 (45min)
9:45 - 10:30 (45min)
Keynote: AI, diagnostic tests and cancer
Michael Blum
›10:30 (30min)
10:30 - 11:00 (30min)
Coffee break
›11:00 (30min)
11:00 - 11:30 (30min)
Self-supervised representation learning on gene expression data for phenotype prediction
Kevin Dradjat
›11:30 (30min)
11:30 - 12:00 (30min)
Learning Single-cell Drug Responses Using Differential Autoencoder Model
Wang Shuhui
›12:00 (30min)
12:00 - 12:30 (30min)
scPRINT: A transcriptomic foundation model for inferring molecular interactions
Jérémie Kalfon
›12:30 (2h)
12:30 - 14:30 (2h)
Lunch and Posters
›14:30 (45min)
14:30 - 15:15 (45min)
Keynote: Deep learning for phylogenetic inference of species diversification
Hélène Morlon
›15:15 (30min)
15:15 - 15:45 (30min)
Transformers for EpiDemiological DYnamics: from genomic data to epidemiological parameters
Vincent Garot
›15:45 (30min)
15:45 - 16:15 (30min)
Coffee break
›16:15 (30min)
16:15 - 16:45 (30min)
ProtMamba: a homology-aware but alignment-free protein state space model
Cyril Malbranke
›16:45 (30min)
16:45 - 17:15 (30min)
Expanding the space of self-reproducing RNA using generative probabilistic models
Martin Weigt
›17:15 (15min)
17:15 - 17:30 (15min)
Closing remarks
