Acceleration based Particle Swarm Optimization (APSO) for RNA Secondary Structure Prediction

Abstract

RNA Secondary Structure prediction is one of the most significant research areas in bioinformatics. Many research works have been developed in the area of RNA secondary structure prediction with optimization methods. But there are certain drawbacks still prevailing in the existing optimization methods. To avoid such drawbacks in the existing methods, we have proposed an Acceleration base Particle Swarm Optimization (APSO) algorithm for finding minimum free energy of RNA secondary structures. The experimental result shows that our proposed APSO algorithm efficiently locates the RNA structures. Furthermore, the performance of our proposed APSO algorithm is evaluated by invoking eight benchmark functions and also compared with Genetic Algorithm (GA) and standard Particle Swarm Optimization (PSO). The test result shows that the APSO is efficient both in test benchmark functions and prediction model and better than other algorithms.