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 information.

Objective: To study R,,NA secondary structure alignment according to the shortcomings of existing secondary structure alignment algorithms and the characteristics of RNA secondary structure.

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.

中文翻译：

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DSARna：基于数字序列表示的RNA二级结构比对

背景：随着高通量测序应用的增加和发展，对 RNA 一级结构的了解呈指数级增长。而且，RNA的功能是由二级或更高级的RNA结构决定的，相似的结构与相似的功能有关，比如tRNA的二级三叶草结构。因此，RNA 结构比对是计算生物学和生物信息学中准确预测功能的重要课题。然而，传统的RNA结构比对算法存在复杂度高、二级结构信息易丢失等缺点。

目的：针对现有二级结构比对算法的不足，结合RNA二级结构的特点，研究R,,NA二级结构比对。

方法：我们提出了一种新的数字序列 RNA 结构表示算法，名为“DSARna”。然后基于动态规划算法，同时构建评分矩阵和二元路径矩阵。在路径矩阵中识别回溯路径，根据路径长度预测最优结果。