Fig 3. Framework for RNA secondary structure prediction methods with ML-based preprocessing or postprocessing.

In RNA secondary structure prediction, ML models (trained by sequence data, in green) can be also used in pretreatment for selecting an appropriate prediction method or a group of appropriate parameters; ML models (trained by structure data, in brown) also can provide a means of determining the most likely structures among the outcomes.