An Evolving Automaton for RNA Secondary Structure Prediction

Conventional methods for RNA 2D structure prediction search for minimal free energy structures. RNA´s, however, RNA´s do not always adopt global minimum structures. Rather, their structure is the result of the folding pathway followed by the structure in nature, which adopts sub-optimal folds occurring along the pathway. Our algorithm consists of an automaton that generates RNA structures by searching for optimal folding pathways. The automaton is endowed of operations to travel throughout the hyperspace of conformers embedded in a base pairing matrix. Using genetic programming it evolves optimizing its ability to find optimal pathways and finally 2D structures. Comparing the evolving automaton with conventional methods shows its potential.