DSARna: RNA Secondary Structure Alignment Based on Digital Sequence Representation

Background: With increasing applications and development of high-throughput sequencing, knowledge of the primary structure of RNA has expanded exponentially. Moreover, the function of RNA is determined by the secondary or higher RNA structure, and similar structures are related to similar functions, such as the secondary clover structure of tRNA. Therefore, RNA structure alignment is an important subject in computational biology and bioinformatics to accurately predict function. However, the traditional RNA structure alignment algorithms have some drawbacks such as high complexity and easy loss of secondary structure information. Objective: To study RNA secondary structure alignment according to the shortcomings of existing secondary structure alignment algorithms and the characteristics of RNA secondary structure. Method: We propose a new digital sequence RNA structure representation algorithm named “DSARna” . Then based on a dynamic programming algorithm, the scoring matrix and binary path matrix are simultaneously constructed. The backtracking path is identified in the path matrix, and the optimal result is predicted according to the path length. Conclusions: Upon comparison with the existing SimTree algorithm through experimental analysis, the proposed method showed higher accuracy and could ensure that the structural information is not easily lost in terms of improved specificity, sensitivity, and the Matthews correlation coefficient.