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Comparison of HSRNAFold and RNAFold Algorithms for RNA Secondary Structure Prediction

机译:HSRNAFOLD和RNAFOLD算法对RNA二级结构预测的比较

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Ribonucleic Acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function. Current physical methods for structure determination are time-consuming and expensive, thus the methods for the computational prediction of structure are necessary. Various algorithms that have been used for RNA structure prediction based in minimum free energy include dynamic programming (DP) and meta heuristic algorithms. One of the most recent meta heuristic algorithms is Musician's behavior-inspired harmony search (HS) algorithm that has been successful in numerous complex optimization problems. This paper builds on the previous work of the harmony search algorithm (HSRNAFold) which was used to find the RNA secondary structure with minimum free energy. In this paper, the accuracy of prediction is compared to the dynamic programming technique RNAFold. The results show that HSRNAFold is able to predict more accurate structures than RNAFold for all test sequences.
机译:核糖核酸(RNA)在细胞中具有重要的结构和功能作用,并在许多蛋白质合成阶段中起作用。 RNA的结构在很大程度上决定了其功能。目前的结构测定物理方法是耗时和昂贵的,因此需要对结构计算预测的方法是必要的。已经基于最小自由能量的RNA结构预测的各种算法包括动态编程(DP)和元启发式算法。最新的元启发式算法之一是音乐家的行为启发的和声搜索(HS)算法在许多复杂的优化问题中成功。本文建立了与最近的和谐搜索算法(HSRNAFOLD)的工作建立在用于找到具有最小自由能的RNA二级结构。在本文中,将预测的准确性与动态编程技术进行了比较,RNAFold。结果表明,Hsrnafold能够预测所有测试序列的rnafold的结构更精确的结构。

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