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A grammar-based approach to RNA pseudoknotted structure prediction for aligned sequences

机译:基于语法的比对序列RNA假结结构预测方法

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A grammatical approach is proposed to predict RNA secondary structures including pseudoknots. The method is based on comparative sequence analysis, i.e., a prediction algorithm accepts a multiple alignment of RNA sequences. We use a stochastic multiple context-free grammar (SMCFG), which can precisely express a wide class of pseudoknots. The probability parameters for the SMCFG can be computed directly from aligned sequences. The experimental results show that the prediction performance of the proposed method is fairly high.
机译:提出了一种语法方法来预测包括假结在内的RNA二级结构。该方法基于比较序列分析,即预测算法接受RNA序列的多重比对。我们使用随机的多上下文无关文法(SMCFG),它可以精确地表达各种伪结。可以直接从比对序列中计算出SMCFG的概率参数。实验结果表明,该方法的预测性能较高。

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