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Aligning alignments exactly

机译:精确对齐路线

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摘要

A basic computational problem that arises in both the construction and local-search phases of the best heuristics for multiple sequence alignment is that of aligning the columns of two multiple alignments. When the scoring function is the sum-of-pairs objective and induced pairwise alignments are evaluated using linear gap-costs, we call this problem Aligning Alignments. While seemingly a straightforward extension of two-sequence alignment, we prove it is actually NP-complete. As explained in the paper, this provides the first demonstration that minimizing linear gap-costs, in the context of multiple sequence alignment, is inherently hard.We also develop an exact algorithm for Aligning Alignments that is remarkably efficient in practice, both in time and space. Even though the problem is NP-complete, computational experiments on both biological and simulated data show we can compute optimal alignments for all benchmark instances in two standard datasets, and solve very-large random instances with highly-gapped sequences.
机译:在针对多个序列比对的最佳试探法的构造阶段和局部搜索阶段中出现的基本计算问题是对两个多重比对的列进行比对的问题。当计分函数是对的总和目标,并且使用线性缺口成本评估诱导的成对比对时,我们称此问题为比对比对。虽然看似两序列比对的直接扩展,但我们证明它实际上是NP完全的。如本文所述,这提供了第一个证明,即在多序列比对的情况下最小化线性缺口成本本质上是困难的。我们还开发了一种精确算法,用于比对,该算法非常有效在实践中,在时间和空间上都是如此。即使问题是NP完全问题,对生物学和模拟数据的计算实验也表明,我们可以为两个标准数据集中的所有基准实例计算最佳比对,并使用高度空缺的序列求解非常大的随机实例。

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