A study of different annealing schedules in SARNA-predict A permutation based SA algorithm for RNA folding

Purpose–The purpose of this paper is to present a study of the effect of different types of annealing schedules for a ribonucleic acid(RNA)secondary structure prediction algorithm based on simulated annealing(SA).Design/methodology/approach–An RNA folding algorithm was implemented that assembles the final structure from potential substructures(helixes).Structures are encoded as a permutation of helixes.An SA searches this space of permutations.Parameters and annealing schedules were studied and fine-tuned to optimize algorithm performance.Findings–In comparing with mfold,the SA algorithm shows comparable results(in terms of F-measure)even with a less sophisticated thermodynamic model.In terms of average specificity,the SA algorithm has provided surpassing results.Research limitations/implications–Most of the underlying thermodynamic models are too simplistic and incomplete to accurately model the free energy for larger structures.This is the largest limitation of free energy-based RNA folding algorithms in general.Practical implications–The algorithm offers a different approach that can be used in practice to fold RNA sequences quickly.Originality/value–The algorithm is one of only two SA-based RNA folding algorithms.The authors use a very different encoding,based on permutation of candidate helixes.The in depth study of annealing schedules and other parameters makes the algorithm a strong contender.Another benefit is that new thermodynamic models can be incorporated with relative ease(which is not the case for algorithms based on dynamic programming).