Review of machine learning methods for RNA secondary structure prediction
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.