Programmable design of functional proteins from natural language
16B-parameter model for designing functional proteins from natural language, with experimental validation across four protein tasks.
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16B-parameter model for designing functional proteins from natural language, with experimental validation across four protein tasks.
Learns domain co-occurrence patterns to guide multidomain protein design beyond the PDB.
No-code Colab platform for training, sharing, and collaborating on protein ML models.
Trimodal contrastive model unifying sequence, structure, and function text for billion-scale protein search.
Multi-agent system orchestrating dynamic computational workflows from 65+ protein engineering tools.
ESM-1b semantic mining discovers multicopper oxidases with superior catalytic and environmental-remediation properties from UniProt.
Interactive protein-language model answering natural-language queries over sequence and structure.
Protocol for PLM-guided TDG optimization with zero-shot prediction and experimental validation.
PLM-guided optimization enables programmable T→G/C base editing with few-shot validation.
General-purpose PLM with structure-aware vocabulary trained on ~40M sequence–structure pairs.