Computer and Automation Research Institute, Hungarian Academy of Sciences, Lágymányosi u 11, 1111 Budapest, Hungary.
BMC Bioinformatics. 2010 Nov 23;11:570. doi: 10.1186/1471-2105-11-570.
In this paper, we introduce a progressive corner cutting method called Reticular Alignment for multiple sequence alignment. Unlike previous corner-cutting methods, our approach does not define a compact part of the dynamic programming table. Instead, it defines a set of optimal and suboptimal alignments at each step during the progressive alignment. The set of alignments are represented with a network to store them and use them during the progressive alignment in an efficient way. The program contains a threshold parameter on which the size of the network depends. The larger the threshold parameter and thus the network, the deeper the search in the alignment space for better scored alignments.
We implemented the program in the Java programming language, and tested it on the BAliBASE database. Reticular Alignment can outperform ClustalW even if a very simple scoring scheme (BLOSUM62 and affine gap penalty) is implemented and merely the threshold value is increased. However, this set-up is not sufficient for outperforming other cutting-edge alignment methods. On the other hand, the reticular alignment search strategy together with sophisticated scoring schemes (for example, differentiating gap penalties for hydrophobic and hydrophylic amino acids) overcome FSA and in some accuracy measurement, even MAFFT. The program is available from http://phylogeny-cafe.elte.hu/RetAlign/
Reticular alignment is an efficient search strategy for finding accurate multiple alignments. The highest accuracy achieved when this searching strategy is combined with sophisticated scoring schemes.
在本文中,我们介绍了一种渐进式的角切割方法,称为网状对齐,用于多序列比对。与以前的角切割方法不同,我们的方法没有定义动态规划表的紧凑部分。相反,它在渐进对齐的每个步骤定义一组最佳和次优的对齐。这些对齐的集合通过网络表示,以便在渐进对齐过程中以有效的方式存储和使用它们。程序包含一个阈值参数,该参数的大小取决于网络。阈值参数越大,网络越大,在对齐空间中的搜索就越深,以获得更好得分的对齐。
我们使用 Java 编程语言实现了该程序,并在 BAliBASE 数据库上进行了测试。即使实现了非常简单的评分方案(BLOSUM62 和仿射间隙罚分),并且仅增加阈值,网状对齐也可以优于 ClustalW。然而,这种设置不足以优于其他前沿的对齐方法。另一方面,网状对齐搜索策略与复杂的评分方案(例如,区分疏水性和亲水性氨基酸的间隙罚分)相结合,克服了 FSA,并且在某些准确性测量方面,甚至超过了 MAFFT。该程序可从 http://phylogeny-cafe.elte.hu/RetAlign/ 获得。
网状对齐是一种用于寻找准确的多重比对的有效搜索策略。当这种搜索策略与复杂的评分方案结合使用时,可以获得最高的准确性。