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Two new distance based methods for phylogenetic tree reconstruction

机译:两种基于距离的系统树重建新方法

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Phylogenetic tree reconstruction is a fundamental problem in biology. In this paper, we propose two new distance based methods for phylogenetic tree reconstruction. One is called double selecting (DS) method. Gronau and Moran (J. Comput. Biol., 14 (2007): 1–5) proposed a Deepest Least Common Ancestor (DLCA) method for phylogenetic tree reconstruction. Our another method is modified version of DLCA and called mDLCA method. Using some data sets, we study the accuracy of these two methods in obtaining the correct unrooted tree in comparison with that of three other tree-making methods: the neighbor-joining (NJ) method, the unweighted pair group (UPGMA) method and DLCA algorithms. The results show that the DS method and mDLCA method perform same well as the NJ method, and are better than UPGMA and DLCA methods. Especially, the DS method even is slightly better than the NJ method in some cases.
机译:系统发育树的重建是生物学中的一个基本问题。在本文中,我们提出了两种基于距离的系统树重建新方法。一种称为双重选择(DS)方法。 Gronau和Moran(J. Comput。Biol。,14(2007):1-5)提出了一种最深的最小公祖(DLCA)方法,用于系统树的重建。我们的另一种方法是DLCA的修改版本,称为mDLCA方法。通过使用一些数据集,我们与其他三种树木制作方法(邻居加入(NJ)方法,非加权对组(UPGMA)方法和DLCA)相比,研究了这两种方法获得正确的无根树的准确性。算法。结果表明,DS方法和mDLCA方法的性能与NJ方法相同,并且优于UPGMA和DLCA方法。特别是在某些情况下,DS方法甚至比NJ方法稍好。

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