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Faster computation of the Robinson-Foulds distance between phylogenetic networks

机译:系统发育网络之间的Robinson-Foulds距离的更快计算

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摘要

The Robinson-Foulds distance, a widely used metric for comparing phylogenetic trees, has recently been generalized to phylogenetic networks. Given two phylogenetic networks N _1, N _2 with n leaf labels and at most m nodes and e edges each, the Robinson-Foulds distance measures the number of clusters of descendant leaves not shared by N _1 and N _2. The fastest known algorithm for computing the Robinson-Foulds distance between N _1 and N _2 runs in O(me) time. In this paper, we improve the time complexity to O(ne/log n) for general phylogenetic networks and O(nm/log n) for general phylogenetic networks with bounded degree (assuming the word RAM model with a word length of ?logn? bits), and to optimal O(m) time for leaf-outerplanar networks as well as optimal O(n) time for level-1 phylogenetic networks (that is, galled-trees). We also introduce the natural concept of the minimum spread of a phylogenetic network and show how the running time of our new algorithm depends on this parameter. As an example, we prove that the minimum spread of a level-k network is at most k + 1, which implies that for one level-1 and one level-k phylogenetic network, our algorithm runs in O((k + 1)e) time.
机译:Robinson-Foulds距离是一种广泛用于比较系统树的度量标准,最近已推广到系统发生网络。给定两个系统发育网络N _1,N _2,它们具有n个叶标签,并且每个节点最多m个节点和e个边缘,Robinson-Foulds距离测量的是N _1和N _2不共享的后代叶片簇的数量。用于计算N _1和N _2之间的Robinson-Foulds距离的最快已知算法以O(me)时间运行。在本文中,我们将系统系统的时间复杂度提高到O(ne / log n),将系统系统的时间复杂度提高到O(nm / log n)有界度(假设单词RAM模型的字长为?logn?位),并为叶外平面网络的最佳O(m)时间以及为1级系统发育网络(即,树)的最佳O(n)时间。我们还介绍了系统进化网络最小传播的自然概念,并展示了我们新算法的运行时间如何取决于此参数。例如,我们证明了k级网络的最小扩展度最多为k + 1,这意味着对于一个1级和一个k级系统发生网络,我们的算法在O((k + 1) e)时间。

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