Near optimal multiple sequence alignments using a traveling salesman problem approach

C. Korostensky, G. Gonnet
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引用次数: 20

Abstract

We present a new method for the calculation of multiple sequence alignments (MSAs). The input to our problem are n protein sequences. We assume that the sequences are related with each other and that there exists some unknown evolutionary tree that corresponds to the MSA. One advantage of our method is that the scoring can be done with reference to this phylogenetic tree, even though the tree structure itself may remain unknown. Instead of computing an evolutionary tree, we only need to compute a circular tour of the tree which is determined via a traveling salesman problem (TSP) algorithm. Our algorithm can calculate a near optimal MSA and has a performance guarantee of n-1/n.opt (where opt is the optimal score of the MSA). The algorithm runs in O(k/sup 2/n/sup 2/) time, where k is the length of the longest input sequence. From there, we improve the alignment further. Experimental results are shown at the end.
基于旅行商问题的近最优多序列对齐方法
提出了一种计算多序列比对(msa)的新方法。我们问题的输入是n个蛋白质序列。我们假设这些序列是相互关联的,并且存在一些未知的与MSA对应的进化树。我们的方法的一个优点是,评分可以参考这个系统发育树,即使树本身的结构可能仍然未知。我们不需要计算进化树,而只需要计算通过旅行推销员问题(TSP)算法确定的树的循环行程。我们的算法可以计算出一个接近最优的MSA,并且具有n-1/n的性能保证。opt(其中opt是MSA的最优分数)。算法运行时间为O(k/sup 2/n/sup 2/),其中k为最长输入序列的长度。在此基础上,我们进一步改进对齐。最后给出了实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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