Argonne National Laboratory

Biomolecular sequence-structure co-design that plans over frozen folding and inverse-folding models with Monte Carlo tree search, training nothing.

Generative histopathology foundation model: a diffusion transformer trained on 30M H&E tiles, conditioned on self-supervised slide embeddings.

Learned compression autoencoders for histopathology whole-slide images, tuned so reconstructions preserve the features downstream models rely on.

Cell-type-specific gene expression prediction from DNA sequence, mapping Enformer epigenomic features to pseudobulk expression for cell-resolved TWAS.

Protein language model that annotates intrinsically disordered regions per residue from sequence alone, without MSAs or biophysical features.

Genome-scale language model trained on prokaryotic genes and SARS-CoV-2 genomes to model viral evolution and flag emerging variants of concern.