Genetic Algorithm based Optimizer for RNA Secondary Structure Prediction

Abstract

paper represents the optimization of RNA secondary structure prediction in RNA molecule by using the genetic algorithm based on binary crossover operators. Using the selection function STDS keep best reproduction for RNA prediction. Take the number of individual RNA sequence sets from the Rfam family database and calculate the lowest free- energy in the individual RNA sequence sets. Apply the fitness function for optimize the lowest free-energy in the each individual sequence sets. Which one individual sequence set have the lowest free-energy that individual sequence set will be predict the best optimizer secondary structure in the RNA individual sequence and used the RNA fold algorithm for calculating the free-energy in the RNA molecules. KeywordsAlgorithm, RNA secondary structure, RNA folding, minimum free-energy, Genetic algorithm representation, Genetic algorithm crossover operators.