An Optimization Algorithm Based on Harmony Search for RNA Secondary Structure Prediction

Abstract

The determination of RNA molecules function relies heavily on its secondary structure. The current physical methods for RNA structure determination are time consuming and expensive. Hence, the methods of computational prediction of structure are the better alternatives. Various algorithms have been used for the RNA structure prediction, including dynamic programming and meta-heuristic algorithms. This chapter proposes the meta-heuristic harmony search algorithm (HSRNAFold) to find RNA secondary structure with minimum free energy and similarity to the native structure. HSRNAFold is compared to dynamic programming techniques: RNAFold and the benchmark, Mfold. The results show that HSRNAFold is comparable to dynamic programming in finding the minimum free energies in all RNA test sequences. The proposed method is efficient and promising in predicting the RNA secondary structure based on the minimum free energy.