Class Information Couple With Free Combination Of Stem For Predicting RNA Secondary Structure

RNA's secondary structure prediction is one of the most important problems in computational molecular biology. It pays an important role in Biomedicine and exploring the origin of life. According to different angles of analyzing problem, they can be basically divided into two categories. One is comparative methods, the other is MFE. However these methods are still not perfect in both efficiency and accuracy. This paper will focus on the shortcomings of existing studies.Firstly, This paper analyses international status of RNA's secondary structure prediction, this paper analyses the characteristics of existing studies. An aim at some problems of existing algorithms, this paper proposes a new method adding the class information for RNA's secondary structure prediction.Thirdly, propose add the class information during the process of free combination of stem RNA's secondary structure prediction. Using centroid of helix, the class information of RNA prediction will be mapped to the coordinate system of class information. The stems with the same type of RNA mapped to the coordinate will show certain regularity, which is included in several different circles of stems. By extracting RNA's class information and joining it in the form of weight during the process of stems'free combination, a multi-tree of class information will be formed. Traversing the tree and finding the branch of which the free energy is minimal, RNA's secondary structure will be acquired. Finally, this paper gives the experimental evaluations of the algorithms proposed in this paper, compares and analyzes the experimental results with existing algorithms, and also makes the conclusions and prospects for the further research.