A heuristic algorithm for RNA secondary structure based on genetic algorithm

Ribonucleic acid (RNA) has an essential and an important role in cellular life. Their functions are directly related to their secondary and tertiary structures. For this reason, RNA structure prediction is one of the most important topics in bioinformatics. X-Ray, Crystallography, and Nuclear Magnetic Resonance are the current physics methods used to determinate the RNA structures. These methods are very efficient but they are very expensive, they require a lot of efforts and extremely time consuming. Therefore, the use of bioinformatics methods to predict the RNA structure is highly desirable and several methods have been proposed. In this paper, we propose a new algorithm that combines between the Greedy Randomized Adaptive Search Procedure (GRASP) and the Genetic Algorithm principle (GA). To assess the efficacy of our algorithm, we have compared it with some of the well-known algorithms for RNA secondary structure prediction such as RNA structure, IPknot, TT2NE and CyloFold, by using four tests cases TMV, CcTMV, CGMMV and Hs_PrP. The obtained results show clearly the effectiveness of the proposed algorithm.