基于置换距离度量的蛋白质多序列比对算法性能评估

 蛋白质多序列比对是一种重要的生物信息学工具，在生物的进化分析以及蛋白质的结构预测方面有着重要的应用。各种比对算法在这个领域都取得了很大的成功，但是每种算法都有其固有的缺陷。提出置换距离法，对当前流行的几种蛋白质多序列比对算法进行对比评价。由于置换距离法仅关注于不同蛋白质间进化距离的相对次序，而不考虑这些进化距离之间的细微差异，因而得到的评价结论更具有鲁棒性。另外，采用最长公共子序法度量置换距离可以比较准确的反映不同置换之间的差异性。基于该算法，对Dialign， Tcoffee， ClustalW和Muscle多序列比对算法进行了性能评估。

Performance Assessment of Protein Multiple Sequence Alignment Algorithms Based on Permutation Distance Measurement

Protein multiple sequence alignment is an important bioinformatics tools. 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 distance is proposed to evaluate several protein multiple sequence alignment algorithms that are widely used currently. As the permutation distance 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. In addition, the longest common subsequence method can well define the distances between different permutations. Using these methods, we compared and assessed Dialign, Tcoffee, ClustalW and Muscle.