CentroidHomfold-LAST: accurate prediction of RNA secondary structure using automatically collected homologous sequences.
CentroidHomfold-LAST: accurate prediction of RNA secondary structure using automatically collected homologous sequences.
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DOI：
10.1093/nar/gkr290
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发表时间：
2011-07
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;Yamada K;Sato K;Frith MC;Asai K
尽管单个 RNA 序列的二级结构预测已广泛应用于许多 RNA 序列分析中，但准确性仍然有限。最近，我们提出了一种方法（称为“CentroidHomfold”），它将同源序列的信息纳入目标序列二级结构的预测中，并表明它大大提高了二级结构预测的性能。然而，CentroidHomfold 强制用户准备目标序列的同源序列。我们开发了一个 Web 应用程序 (CentroidHomfold-LAST)，它使用自动收集的同源序列来预测目标序列的二级结构。 Web 应用程序中采用了 LAST（一种快速且灵敏的局部对准器）和 CentroidHomfold。使用常用数据集的计算实验表明，CentroidHomfold-LAST 大大优于包括 CentroidFold 和 RNAfold 在内的传统二级结构预测。
Although secondary structure predictions of an individual RNA sequence have been widely used in a number of sequence analyses of RNAs, accuracy is still limited. Recently, we proposed a method (called ‘CentroidHomfold’), which includes information about homologous sequences into the prediction of the secondary structure of the target sequence, and showed that it substantially improved the performance of secondary structure predictions. CentroidHomfold, however, forces users to prepare homologous sequences of the target sequence. We have developed a Web application (CentroidHomfold-LAST) that predicts the secondary structure of the target sequence using automatically collected homologous sequences. LAST, which is a fast and sensitive local aligner, and CentroidHomfold are employed in the Web application. Computational experiments with a commonly-used data set indicated that CentroidHomfold-LAST substantially outperformed conventional secondary structure predictions including CentroidFold and RNAfold.
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影响因子：
14.9
作者：
Hamada M;Sato K;Asai K
通讯作者：
Asai K
影响因子：
3.7
作者：
Hamada M;Kiryu H;Iwasaki W;Asai K
通讯作者：
Asai K
影响因子：
14.9
作者：
Ding, Y;Chan, CY;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：
7
作者：
Kielbasa, Szymon M.;Wan, Raymond;Frith, Martin C.
通讯作者：
Frith, Martin C.