Models (7)
Guided discrete diffusion model for antibody lead optimization, conditioning sequence design on the seed binder's CDR canonical backbone conformation.
Genomics foundation model that unifies sequence-to-function prediction, DNA language modeling, and generative regulatory design in one backbone.
Latent diffusion model for controllable all-atom protein generation that co-designs sequence and structure while training on sequences alone.
Single-cell foundation model trained by metric learning to embed scRNA-seq profiles for cell type annotation and similarity search in cell atlases.
Efficient protein language model library from Prescient Design enabling high-quality sequence representations and fitness prediction in 24 GPU hours.
Discrete generative model for antibody protein sequences combining MCMC walks on a smoothed energy landscape with one-step denoising jumps.
Protein structure prediction model pairing SE(3)-equivariant networks with a coarse-grained representation to fold sequences fast, without MSA inputs.