Csurös Miklós
Department of Computer Science, Yale University, New Haven, CT 06520, USA.
J Comput Biol. 2002;9(2):277-97. doi: 10.1089/10665270252935467.
We present a novel distance-based algorithm for evolutionary tree reconstruction. Our algorithm reconstructs the topology of a tree with n leaves in O(n(2)) time using O(n) working space. In the general Markov model of evolution, the algorithm recovers the topology successfully with (1 - o(1)) probability from sequences with polynomial length in n. Moreover, for almost all trees, our algorithm achieves the same success probability on polylogarithmic sample sizes. The theoretical results are supported by simulation experiments involving trees with 500, 1,895, and 3,135 leaves. The topologies of the trees are recovered with high success from 2,000 bp DNA sequences.
我们提出了一种用于进化树重建的基于距离的新算法。我们的算法使用O(n)的工作空间,在O(n(2))时间内重建具有n个叶节点的树的拓扑结构。在一般的马尔可夫进化模型中,该算法能以(1 - o(1))的概率从长度为n的多项式序列中成功恢复拓扑结构。此外,对于几乎所有的树,我们的算法在多对数样本大小上能达到相同的成功概率。理论结果得到了涉及具有500、1895和3135个叶节点的树的模拟实验的支持。从2000 bp的DNA序列中能以高成功率恢复树的拓扑结构。