University of North Carolina at Chapel Hill

Message-passing neural network that designs buried hydrogen-bond networks onto protein backbones, combining learned placement with PyRosetta scoring.

Cell world model pretrained on a 2.4M-cell mouse embryonic atlas, predicting one-step transcriptional state transitions and perturbation response.

fMRI foundation model of the human brain connectome: 1.2B parameters and brain-environment interaction tokens for behavior and disease prediction.

Structure-aware adapter that injects chromatin-derived gene regulatory networks into single-cell RNA foundation models like scGPT and scFoundation.

Medical image segmentation model that replaces MedSAM's manual box prompts with a diffusion prompt encoder and labels each mask by class.

Cryo-EM reconstruction with neural radiance fields in Euclidean 3D space, separating conformational motion from compositional assembly states.

Tissue-aware foundation model that restores brain MRI quality across motion correction, super-resolution, denoising, and harmonization.

RNA foundation language model pretrained on mammalian and viral genomes, fine-tuned to predict translation efficiency, half-life, and splice sites.

Foundation model for medical image registration that aligns CT and MRI across anatomies and modalities without per-pair optimization or retraining.

Renal pathology segmentation covering six kidney tissue types across 5x to 40x magnifications from one network, and transferring from human to mouse.