Comparison of HSRNAFold and RNAFold algorithms for RNA secondary structure prediction

Ribonucleic acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function. Current physical methods for structure determination are time-consuming and expensive, thus the methods for the computational prediction of structure are necessary. Various algorithms that have been used for RNA structure prediction based in minimum free energy include dynamic programming (DP) and meta heuristic algorithms. One of the most recent meta heuristic algorithms is Musician's behavior-inspired harmony search (HS) algorithm that has been successful in numerous complex optimization problems. This paper builds on the previous work of the harmony search algorithm (HSRNAFold) which was used to find the RNA secondary structure with minimum free energy. In this paper, the accuracy of prediction is compared to the dynamic programming technique RNAFold. The results show that HSRNAFold is able to predict more accurate structures than RNAFold for all test sequences.