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Predicting a set of minimal free energy RNA secondary structures common to two sequences

机译:预测两个序列共有的一组最小自由能RNA二级结构

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Motivation: Function derives from structure, therefore, there is need for methods to predict functional RNA structures.Results: The Dynalign algorithm, which predicts the lowest free energy secondary structure common to two unaligned RNA sequences, is extended to the prediction of a set of low-energy structures. Dot plots can be drawn to show all base pairs in structures within an energy increment. Dynalign predicts more well-defined structures than structure prediction using a single sequence; in 5S rRNA sequences, the average number of base pairs in structures with energy within 20% of the lowest energy structure is 317 using Dynalign, but 569 using a single sequence. Structure prediction with Dynalign can also be constrained according to experiment or comparative analysis. The accuracy, measured as sensitivity and positive predictive value, of Dynalign is greater than predictions with a single sequence.
机译:动机:功能源自结构,因此,需要预测功能性RNA结构的方法。结果:Dynalign算法可预测两个未比对的RNA序列共有的最低自由能二级结构,可扩展到预测一组低能结构。可以绘制点图以显示能量增量内结构中的所有碱基对。与使用单个序列进行结构预测相比,Dynalign预测结构更清晰。在5S rRNA序列中,使用Dynalign的能量在最低能量结构的20%以内的结构中,平均碱基对数目为317,而使用单个序列为569。 Dynalign的结构预测也可以根据实验或比较分析进行约束。 Dynalign的灵敏度(灵敏度和阳性预测值)衡量的准确性高于单个序列的预测。

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