Fig 4. Framework for the RNA secondary structure prediction methods with ML-based prediction process.

ML models (trained by wet lab, RNA sequence, or RNA structure data) are directly used to predict RNA secondary structures in an end-to-end way or followed by a filter or optimizer to obtain the optimal RNA secondary structure.