Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix.
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix.
复制标题
通过修剪动力学编程矩阵，快速成对的结构RNA对齐。
DOI：
10.1371/journal.pcbi.0030193
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发表时间：
2007-10
影响因子：
4.3
通讯作者：
Gorodkin, Jan
中科院分区：
文献类型：
--
作者：
Havgaard, Jakob H.;Torarinsson, Elfar;Gorodkin, Jan
非编码RNA（noncoding RNA，ncRNA）在细胞中发挥着重要作用，研究表明哺乳动物基因组中可能存在大量未知的ncRNA。存在可用于通过比较来自不同基因组的序列来搜索ncRNA的计算方法。这些方法的一个主要问题是它们的计算复杂性，因此采用了几何学。目前有两种方法非常流行：预折叠和预对齐。然而，这些化学分析并不理想，因为预比对依赖于可能不存在的序列相似性，而预折叠忽略了比较信息。在这里，修剪的动态规划矩阵作为一种替代新的启发式约束。当矩阵被填充时，不超过长度相关的最小分数的所有子比对被丢弃，从而给出动态提供约束的优点。这已被包括在一个新的实现的FOLDALIGN算法成对的局部或全局结构比对的RNA序列。结果表明，时间和内存的要求显着降低，同时保持整体性能。此外，提出了一种分而治之的方法来限制全局对齐和局部对齐回溯过程中的内存需求。找到计算的RNA结构中的所有分支点，并将其用于将结构划分为较小的无分支片段。然后以正常方式重新对齐和回溯每个段。最后，FOLDALIGN算法也进行了更新，具有更好的内存实现和改进的能量模型。通过对算法的这些改进，FOLDALIGN软件包为分子生物学家提供了一个高效且用户友好的工具来搜索新的ncRNA。该软件包可从http://foldalign.ku.dk下载。FOLDALIGN是一种对RNA序列进行成对结构比对的算法。它使用轻量级能量模型和序列相似性来同时折叠和比对序列。该算法可以进行局部和全局对齐。结构比对方法的强大之处在于，它们可以比对那些一级序列已经偏离太多而使正常比对方法无法使用的序列。通过结构比对方法预测的结构通常比通过单序列折叠方法预测的结构更好，因为它们可以考虑比较信息。大多数结构对齐方法的主要问题是它们在计算上太昂贵。在本文中，我们介绍了动态修剪启发式，使FOLDALIGN方法显着更快，而不降低预测性能。内存要求也显著降低，允许分析更长的序列。该算法的一个用户友好的（尽管仍然是基于命令行的）实现可以从以下网站获得：http://foldalign.ku.dk
It has become clear that noncoding RNAs (ncRNA) play important roles in cells, and emerging studies indicate that there might be a large number of unknown ncRNAs in mammalian genomes. There exist computational methods that can be used to search for ncRNAs by comparing sequences from different genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained. Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool for searching for new ncRNAs. The software package is available for download at http://foldalign.ku.dk. FOLDALIGN is an algorithm for making pairwise structural alignments of RNA sequences. It uses a lightweight energy model and sequence similarity to simultaneously fold and align the sequences. The algorithm can make local and global alignments. The power of structural alignment methods is that they can align sequences where the primary sequences have diverged too much for normal alignment methods to be useful. The structures predicted by structural alignment methods are usually better than the structures predicted by single-sequence folding methods since they can take comparative information into account. The main problem for most structural alignment methods is that they are too computationally expensive. In this paper we introduce the dynamical pruning heuristic that makes the FOLDALIGN method significantly faster without lowering the predictive performance. The memory requirements are also significantly lowered, allowing for the analysis of longer sequences. A user-friendly (still command-line based, though) implementation of the algorithm is available at the Web site: http://foldalign.ku.dk
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影响因子：
3
作者：
Harmanci AO;Sharma G;Mathews DH
通讯作者：
Mathews DH
影响因子：
3.1
作者：
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作者：
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影响因子：
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作者：
D Dowell, Robin;Eddy, Sean R.
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Eddy, Sean R.
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5.8
作者：
Havgaard, JH;Lyngso, RB;Gorodkin, J
通讯作者：
Gorodkin, J