Performance assessment of protein multiple sequence alignment algorithms based on permutation similarity measurement.
Performance assessment of protein multiple sequence alignment algorithms based on permutation similarity measurement.
复制标题
基于排列相似性测量的蛋白质多序列比对算法的性能评估。
DOI：
10.1016/j.bbrc.2010.07.103
复制
发表时间：
2010
影响因子：
3.1
通讯作者：
Liuhuan Dong
中科院分区：
文献类型：
--
作者：
Zhi Gong;Fang;Liuhuan Dong
蛋白质多序列比对是一种重要的生物信息学工具。它在生物进化分析和蛋白质结构预测中有重要的应用。各种对齐算法在这一领域取得了巨大的成功。然而，每种算法都有其固有的缺陷。本文提出用排列相似度来评价目前广泛使用的几种蛋白质多序列比对算法。由于置换相似性方法只考虑不同蛋白质进化距离的相对顺序，而不考虑进化距离之间的微小差异，因此可以得到更稳健的评价结果。采用最长公共子序列方法定义不同排列之间的相似度。使用这些方法，我们评估了Dialign，Tcoffee，ClustalW和Muscle，并进行了比较。
Protein multiple sequence alignment is an important bioinformatics tool. It has important applications in biological evolution analysis and protein structure prediction. A variety of alignment algorithms in this field have achieved great success. However, each algorithm has its own inherent deficiencies. In this paper, permutation similarity is proposed to evaluate several protein multiple sequence alignment algorithms that are widely used currently. As the permutation similarity method only concerns the relative order of different protein evolutionary distances, without taking into account the slight difference between the evolutionary distances, it can get more robust evaluations. The longest common subsequence method is adopted to define the similarity between different permutations. Using these methods, we assessed Dialign, Tcoffee, ClustalW and Muscle and made comparisons among them.
多个 DNA 和蛋白质序列数据的比对。
DOI：
10.1093/bioinformatics/4.1.213
发表时间：
1988
期刊：
Computer applications in the biosciences : CABIOS
影响因子：
--
作者：
Friedemann,T
通讯作者：
Friedemann,T