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An Efficient Alignment Algorithm for Searching Simple Pseudoknots over Long Genomic Sequence

机译:在长基因组序列上搜索简单假结的高效比对算法

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Structural alignment has been shown to be an effective computational method to identify structural noncoding RNA (ncRNA) candidates as ncRNAs are known to be conserved in secondary structures. However, the complexity of the structural alignment algorithms becomes higher when the structure has pseudoknots. Even for the simplest type of pseudoknots (simple pseudoknots), the fastest algorithm runs in O(mn^3) time, where m, n are the length of the query ncRNA (with known structure) and the length of the target sequence (with unknown structure), respectively. In practice, we are usually given a long DNA sequence and we try to locate regions in the sequence for possible candidates of a particular ncRNA. Thus, we need to run the structural alignment algorithm on every possible region in the long sequence. For example, finding candidates for a known ncRNA of length 100 on a sequence of length 50,000, it takes more than one day. In this paper, we provide an efficient algorithm to solve the problem for simple pseudoknots and it is shown to be 10 times faster. The speedup stems from an effective pruning strategy consisting of the computation of a lower bound score for the optimal alignment and an estimation of the maximum score that a candidate can achieve to decide whether to prune the current candidate or not.
机译:已经证明结构比对是鉴定结构非编码RNA(ncRNA)候选物的有效计算方法,因为已知ncRNA在二级结构中是保守的。但是,当结构具有假结时,结构对齐算法的复杂度会更高。即使对于最简单的伪结类型(简单的伪结),最快的算法也可以在O(mn ^ 3)时间内运行,其中m,n是查询ncRNA的长度(具有已知结构)和目标序列的长度(具有结构未知)。在实践中,通常给我们长的DNA序列,我们尝试在序列中定位特定ncRNA可能候选者的区域。因此,我们需要在长序列的每个可能区域上运行结构比对算法。例如,在长度为50,000的序列中找到长度为100的已知ncRNA的候选对象,需要花费超过一天的时间。在本文中,我们提供了一种有效的算法来解决简单的伪结问题,该算法速度提高了10倍。加速源于有效的修剪策略,该策略包括计算最佳对齐方式的下限分数和估算候选人可达到的最大分数估计,以决定是否修剪当前候选人。

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