AntiClustal: Multiple Sequence Alignment by antipole clustering and linear approximate 1-median computation.

C Di Pietro, V Di Pietro, G Emmanuele, A Ferro, T Maugeri, E Modica, G Pigola, A Pulvirenti, M Purrello, M Ragusa, M Scalia, D Shasha, S Travali, V Zimmitti
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引用次数: 0

Abstract

In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.

反簇:通过反极聚类和线性近似1-中位数计算的多序列比对。
本文提出了一种新的多序列比对算法AntiClusAl。该方法利用了常用的思路,即对属于某一聚类算法生成的类的同源序列进行比对,然后沿着合适的树状结构自下而上地进行比对。然后在树的根读取最终结果。每个集群中的多个序列对齐利用与集群的1-中位数(中心)的渐进对齐。序列集合S的1-中位数是S中与S中任何其他序列的平均距离最小的元素,其精确计算需要二次元时间。我们提出的算法的基本思想是利用一种简单而自然的基于随机竞赛的算法技术,该算法已经成功地应用于一般度量空间中的大尺寸搜索问题。特别使用了一种称为反极树的聚类算法和近似线性1-中位数计算。我们的算法与广泛使用的MSA工具Clustal W相比,显示出更好的运行时间结果和完全相同的对齐质量。本文还引用了非洲爪蟾SOD2进化过程中氨基酸高度保守的成功生物学应用。
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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