Improving the accuracy of predicting secondary structure for aligned RNA sequences.
Improving the accuracy of predicting secondary structure for aligned RNA sequences.
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DOI：
10.1093/nar/gkq792
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发表时间：
2011-01
影响因子：
14.9
通讯作者：
Asai K
中科院分区：
文献类型：
--
作者：
Hamada M;Sato K;Asai K
由于预测比对RNA序列的二级结构不仅可用于提高传统二级结构预测的有限准确性，而且可用于发现基因组序列中的非编码RNA，因此已将相当多的注意力集中在预测比对RNA序列的二级结构上。虽然目前已经有很多预测RNA序列二级结构的算法，但其准确性还有待进一步提高。为了提高预测的准确性，本文对目前预测RNA序列二级结构的算法进行了理论分类。该分类基于最大预期准确度（MEA）的观点，该观点已成功应用于生物信息学中的各种问题。分类揭示了当前算法的几个缺点，但我们提出了一个改进的以前介绍的算法（CentroidAlifold）。最后，计算实验有力地支持了理论分类，并表明改进的CentroidAlifold大大优于其他算法。
Considerable attention has been focused on predicting the secondary structure for aligned RNA sequences since it is useful not only for improving the limiting accuracy of conventional secondary structure prediction but also for finding non-coding RNAs in genomic sequences. Although there exist many algorithms of predicting secondary structure for aligned RNA sequences, further improvement of the accuracy is still awaited. In this article, toward improving the accuracy, a theoretical classification of state-of-the-art algorithms of predicting secondary structure for aligned RNA sequences is presented. The classification is based on the viewpoint of maximum expected accuracy (MEA), which has been successfully applied in various problems in bioinformatics. The classification reveals several disadvantages of the current algorithms but we propose an improvement of a previously introduced algorithm (CentroidAlifold). Finally, computational experiments strongly support the theoretical classification and indicate that the improved CentroidAlifold substantially outperforms other algorithms.
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DOI：
10.1089/cmb.2008.0137
发表时间：
2009-01
期刊：
Journal of computational biology : a journal of computational molecular cell biology
影响因子：
--
作者：
Newberg LA;Lawrence CE
通讯作者：
Lawrence CE
影响因子：
1.8
作者：
HOFACKER, IL;FONTANA, W;SCHUSTER, P
通讯作者：
SCHUSTER, P
影响因子：
1.7
作者：
Holmes, I;Durbin, R
通讯作者：
Durbin, R
影响因子：
5.8
作者：
Kiryu, Hisanori;Kin, Taishin;Asai, Kiyoshi
通讯作者：
Asai, Kiyoshi
影响因子：
14.9
作者：
Knudsen, B;Hein, J
通讯作者：
Hein, J