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Predictions of RNA secondary structure by combining homologous sequence information

机译:通过结合同源序列信息预测RNA二级结构

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Motivation: Secondary structure prediction of RNA sequences is an important problem. There have been progresses in this area, but the accuracy of prediction from an RNA sequence is still limited. In many cases, however, homologous RNA sequences are available with the target RNA sequence whose secondary structure is to be predicted.Results: In this article, we propose a new method for secondary structure predictions of individual RNA sequences by taking the information of their homologous sequences into account without assuming the common secondary structure of the entire sequences. The proposed method is based on posterior decoding techniques, which consider all the suboptimal secondary structures of the target and homologous sequences and all the suboptimal alignments between the target sequence and each of the homologous sequences. In our computational experiments, the proposed method provides better predictions than those performed only on the basis of the formation of individual RNA sequences and those performed by using methods for predicting the common secondary structure of the homologous sequences. Remarkably, we found that the common secondary predictions sometimes give worse predictions for the secondary structure of a target sequence than the predictions from the individual target sequence, while the proposed method always gives good predictions for the secondary structure of target sequences in all tested cases.
机译:动机:RNA序列的二级结构预测是一个重要的问题。该领域已经取得了进展,但是从RNA序列进行预测的准确性仍然受到限制。然而,在许多情况下,同源RNA序列与目标RNA序列可预测其二级结构。结果:在本文中,我们提出了一种新的方法,可通过获取各个RNA序列的同源性信息来预测其二级结构在不假设整个序列具有共同二级结构的情况下考虑序列。所提出的方法基于后验解码技术,其考虑了靶序列和同源序列的所有次优二级结构以及靶序列与每个同源序列之间的所有次优比对。在我们的计算实验中,与仅基于单个RNA序列的形成以及通过使用用于预测同源序列的共同二级结构的方法所进行的预测相比,所提出的方法提供了更好的预测。值得注意的是,我们发现常见的二级预测有时会比单个目标序列的预测对目标序列的二级结构提供更差的预测,而所提出的方法在所有测试情况下始终会对目标序列的二级结构提供良好的预测。

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