ProMORNA uses a BART encoder-decoder pretrained on millions of protein-mRNA pairs followed by multi-objective group relative policy optimization to generate full-length mRNA sequences that improve predicted half-life and translation efficiency over supervised baselines on an unseen luciferase target
DeepSeek-V3.2: Pushing the frontier of open large language models
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Protein-Conditioned Multi-Objective Reinforcement Learning for Full-Length mRNA Design
ProMORNA uses a BART encoder-decoder pretrained on millions of protein-mRNA pairs followed by multi-objective group relative policy optimization to generate full-length mRNA sequences that improve predicted half-life and translation efficiency over supervised baselines on an unseen luciferase target