Models (5)
Latent diffusion model for controllable all-atom protein generation that co-designs sequence and structure while training on sequences alone.
Metric learning foundation model that embeds single-cell RNA-seq profiles into a unified space for scalable cell type annotation and cross-atlas similarity search across tens of millions of cells.
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.
SE(3)-equivariant protein structure prediction model using a novel coarse-grained representation for orders-of-magnitude faster inference.