Washington University in St. Louis

Cell type annotation model mapping human single-cell and spatial transcriptomes onto one hierarchical typology of 381 types across 23 tissues.

Single-cell language model that prepends biomedical knowledge-graph tokens to cell sentences, grounding cell type annotation in pathway structure.

Protein conformational sampling framework that steers a retrained OpenFold with diverse secondary-structure predictions to recover alternative states.

De novo protein design model that co-generates sidechains, backbone, and sequence in one flow-matching process instead of backbone only.

Multimodal graph foundation model fusing single-cell expression, biomedical text, and signaling networks, pretrained on ~80M sc/snRNA-seq profiles.

Disordered protein ensemble prediction from sequence, generating hundreds of conformers in seconds via latent diffusion over distance maps.

Instance segmentation for nervous-system tissue, trained only on biophysical simulations and applied to real brain, spinal cord and nerve sections.