Weber Griffin, Ohno-Machado Lucila, Shieber Stuart
Decision Systems Group, Brigham and Women's Hospital, Division of Health Sciences and Technology, Harvard and MIT, USA.
J Biomed Inform. 2006 Feb;39(1):43-50. doi: 10.1016/j.jbi.2005.11.001. Epub 2005 Nov 28.
Phylogenetic tree reconstruction is a process in which the ancestral relationships among a group of organisms are inferred from their DNA sequences. For all but trivial sized data sets, finding the optimal tree is computationally intractable. Many heuristic algorithms exist, but the branch-swapping algorithm used in the software package PAUP* is the most popular. This method performs a stochastic search over the space of trees, using a branch-swapping operation to construct neighboring trees in the search space. This study introduces a new stochastic search algorithm that operates over an alternative representation of trees, namely as permutations of taxa giving the order in which they are processed during stepwise addition. Experiments on several data sets suggest that this algorithm for generating an initial tree, when followed by branch-swapping, can produce better trees for a given total amount of time.
系统发育树重建是一个从一组生物体的DNA序列推断其祖先关系的过程。对于所有但极小数据集而言,找到最优树在计算上是难以处理的。存在许多启发式算法,但软件包PAUP*中使用的分支交换算法是最受欢迎的。该方法在树的空间上进行随机搜索,使用分支交换操作在搜索空间中构建相邻的树。本研究引入了一种新的随机搜索算法,该算法在树的另一种表示形式上运行,即分类群的排列,给出它们在逐步添加过程中被处理的顺序。对几个数据集的实验表明,这种用于生成初始树的算法,在随后进行分支交换时,在给定的总时间内可以产生更好的树。