From the source
OpenMed built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization.
They trained and compared multiple transformer architectures for codon-level language modeling, finding CodonRoBERTa-large-v2 as the best with perplexity 4.10 and Spearman CAI correlation 0.40.
They scaled to 25 species, training 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers.
