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 predict function accurately. However, the traditional RNA structure alignment
algorithms have some drawbacks such as high complexity and easy loss of secondary structure
Objective: To study R,,NA secondary structure alignment according to the shortcomings of
existing secondary structure alignment algorithms and the characteristics of RNA secondary
Methods: 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