Research On RNA Secondary Structure Prediction Based On Heuristic Optimization

RNA molecule is an important substance in the organism, and it is working together with the DNA molecule and protein to maintain the life activity. As one of the most important carrier of genetic information, RNA plays a key role in the synthesis of protein, gene regulation, enzyme catalysis, cell differentiation etc. Rapid and accurate determination of RNA secondary structure facilitates the understanding of the actual spatial structure, and it has a very important significance for the analysis of RNA molecules in the cell operation mechanism, searching homologous RNA molecules, improving the accuracy of prediction of protein and other aspects.The traditional physics experiment of determining RNA secondary structure is time-consuming and high-cost, which can not meet the development needs. To solve this problem, researchers proposed and comparative sequence analysis method, in which the minimum free energy method is more common. On the basis of this method, the dynamic programming method, the maximum base pairing method and the combination optimization method of the stems are proposed. However, the efficiency of these algorithms is relatively low. Heuristic optimization algorithm is often used to solve combinatorial optimization problems, which can be used to predict the RNA secondary structure. Therefore, this paper introduces the RNA secondary structure involving biological concepts, prediction of RNA secondary structure method research current situation, relevant database, and compare the heuristic optimization algorithm based on, focusing on heuristic based optimization of the advantages and disadvantages of the algorithm is analyzed performance with minimal free, according to RNA secondary structure if they contain pseudoknots seek different heuristic optimization strategy for prediction research. The main contents are as follows:(1)The in-depth study of the application in RNA secondary structure prediction in the field of heuristic optimization algorithm, including the analysis of various algorithms of thought and performance advantages and disadvantages according to secondary structure if it contains a pseudoknot seek different heuristic optimization strategy is to predict. An improved hybrid algorithm GSHA(Simulated Annealing Hybrid Algorithm Genetic) is proposed to predict the RNA secondary structure without pseudoknots.(2) According to the algorithm GSHA, design corresponding experimental scheme, through the simulation experiment of PSTV virus with a length of 359 sequence of secondary structure formation process simulation and the forecast results and RNase P structure database in the actual structure are compared with each other. And the experiment results show that the accuracy of GSHA algorithm is higher than using two algorithms separately.(3) Analyze the characteristics of the pseudoknots and construct the energy model, a tabu search algorithm based on heuristic optimization is proposed to predict the RNA secondary Prediction. The integrity of the solution is maintained by using centralized search for the current approach to the solution space. The simulation experiment selected 8 test sequences, using RNA Predict algorithm as a comparative experiment. The results show that the TSRP algorithm results to predict the accuracy, specificity and time efficiency of the algorithm is higher than the RNA Predict algorithm.