Institut Pasteur

Anti-phage defense gene predictor fusing protein language model embeddings with a contrastive genomic-context transformer over 64-gene windows.

Template-guided 3D ligand pose generation by flow matching plus differentiable refinement, placing 77.8% of poses within 2 Å RMSD on AlignDockBench.

Single-cell foundation model pre-trained on 50 million cells that infers cell-specific gene regulatory networks from transformer attention matrices.

Cell segmentation for image-based spatial transcriptomics that fuses RNA point clouds with any number of membrane and nuclear staining channels.

Protein language model fine-tuned to score any bacterial protein for anti-phage defense function, detecting homology too remote for HMM profiles.

Genomic language model reading bacterial gene neighborhoods as sentences of protein-family tokens to predict anti-phage defense function.

Spike inference from calcium imaging traces, driven by a multistate GCaMP kinetic model that generates the synthetic data its decoders are trained on.

Single-cell foundation model pre-trained on 50 million cells for gene network inference, denoising, and cell type prediction.

RNA virtual screening that reads a binding site's base-pairing graph and predicts the chemical fingerprint of its ligand to rank compound libraries.