Labs & Groups (1)
Models (7)
A Llama 3 model fine-tuned on a ChEMBL corpus that designs molecular linkers from natural-language geometry and physicochemical prompts, without task-specific re-training.
A deep generative model of protein evolution in time that captures indel dynamics and epistasis to simulate realistic evolutionary trajectories yielding functional proteins.
A multimodal framework for text-guided protein design, enabling sequence generation, zero-shot editing, and property prediction via contrastive learning.
Latent diffusion model for controllable all-atom protein generation that co-designs sequence and structure while training on sequences alone.
A DNA language model for unsupervised genome-wide variant effect prediction, trained on multispecies genomes via masked language modeling without functional annotation labels.
Transformer-based DNA language model using whole-genome multispecies alignments for genome-wide variant effect prediction across coding and non-coding regions.
Benchmark suite of five biologically relevant tasks for evaluating protein sequence representation learning, covering structure, homology, and engineering.