Leveraging secondary-structure information for accurate nucleic acid structure prediction with OFoldNA

arXiv:2609.37414 · q-bio.BM · Submitted 2026-09-29 · Read on arXiv

q-bio.BM

Submitted: 2026-09-29

Updated: 2026-10-08

Code: https://github.com/OTeam-AI4S/OFoldNA

Terminology

Accuracy — 14× in this paper · explained in 1 episode
Distillation — 6× in this paper · explained in 2 episodes
F1 Score — 5× in this paper · explained in 3 episodes
Ablation — 4× in this paper · explained in 1 episode
Core — 4× in this paper · explained in 2 episodes
Generalization — 4× in this paper · explained in 13 episodes
Benchmarking — 3× in this paper · explained in 3 episodes
Protein Data Bank — 3× in this paper
Benchmark — 2× in this paper · explained in 2 episodes
Decode — 2× in this paper · explained in 2 episodes
Fidelity — 2× in this paper · explained in 2 episodes
Generalizability — 2× in this paper · explained in 6 episodes
Robustness — 2× in this paper · explained in 5 episodes
Ab Initio — 1× in this paper · explained in 1 episode
Adam — 1× in this paper · explained in 2 episodes
Alignment — 1× in this paper · explained in 1 episode
Computational Biology — 1× in this paper · explained in 2 episodes
Diffusion Model — 1× in this paper · explained in 8 episodes
Flow Matching — 1× in this paper · explained in 8 episodes
Foundation Model — 1× in this paper · explained in 3 episodes
Self-Distillation — 1× in this paper · explained in 7 episodes
Transfer Learning — 1× in this paper · explained in 10 episodes
Transformer — 1× in this paper · explained in 2 episodes
Unified Framework — 1× in this paper · explained in 5 episodes

Sources

Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-structure prediction

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