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    基于隐Markov模型的RNA二级结构预测新方法

    A Method of RNA Secondary Structure Prediction Based on Hidden Markov Model

    • 摘要: 有效预测RNA二级结构是生物信息学中的重要研究领域.提出一种基于隐Markov模型预测RNA二级结构的新方法.首先,应用前后缀匹配算法快速找到所有可能(包括假结)的茎区,建立RNA-HMM,寻找最优的茎区组合方法,得到包含假结的RNA二级结构.实验结果表明,提出的新方法降低了计算复杂性,提高了预测的特异性和敏感性,具有较高的准确率,可以预测RNA的假结结构.

       

      Abstract: The effective prediction of RNA secondary structure is an important research field of bioinformatics. We propose a new method based on hidden Markov model to predict the RNA secondary structure. We appliy the matching algorithm of prefix and suffix to find all the possible (including the pseudo-knot) stem zones quickly, establish the RNA-HMM, find the optimal method of the combination of stem zones, and obtain the RNA secondary structure including the pseudo-knot. The experiment results show that this method can reduce the computational complexity and improve the specificity and sensitivity of prediction with high accuracy, and can also predict the pseudo-knot structure.

       

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