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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method
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PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method

机译：PSRna：基于反向互补折叠法的小RNA二级结构的预测

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摘要

Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named "PSRna" for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs. Unlike traditional algorithms that usually generate multi-branch loops and 50 end self-folding, PSRna first estimated the maximum number of base pairs of RNA secondary structures based on the dynamic programming algorithm and a path matrix is constructed at the same time. Second, the backtracking paths are extracted from the path matrix based on backtracking algorithm, and each backtracking path represents a secondary structure. To improve accuracy, the predicted RNA secondary structures are filtered based on their free energy, where only the secondary structure with the minimum free energy was identified as the candidate secondary structure. Our experiments on real data show that the proposed algorithm is superior to two popular methods, RNAfold and RNAstructure, in terms of sensitivity, specificity and Matthews correlation coefficient (MCC).
机译：RNA二级结构的预测是计算生物学和生物信息学中的重要问题，因为RNA二级结构是RNA分子功能分析的基础。然而，小RNA的二级结构是稀缺的，很少专门设计算法来预测小RNA的二级结构。在这里，我们提出了一种名为“ PSRna”的算法，用于使用反向互补折叠和小RNA的特征性发夹环预测小RNA二级结构。与通常产生多分支环和50个末端自折叠的传统算法不同，PSRna首先根据动态编程算法估算RNA二级结构的最大碱基对数目，并同时构建路径矩阵。其次，基于回溯算法从路径矩阵中提取回溯路径，每个回溯路径代表一个二级结构。为了提高准确性，根据预测的RNA二级结构的自由能进行过滤，其中只有具有最小自由能的二级结构才被识别为候选二级结构。我们在真实数据上的实验表明，该算法在敏感性，特异性和马修斯相关系数（MCC）方面优于两种流行的方法，RNAfold和RNAstructure。

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