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从最短类群间距离信息中恢复正常网络

Recovering normal networks from shortest inter-taxa distance information.

作者信息

Bordewich Magnus, Huber Katharina T, Moulton Vincent, Semple Charles

机构信息

Department of Computer Science, Durham University, Durham, DH1 3LE, UK.

School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.

出版信息

J Math Biol. 2018 Sep;77(3):571-594. doi: 10.1007/s00285-018-1218-x. Epub 2018 Feb 24.

Abstract

Phylogenetic networks are a type of leaf-labelled, acyclic, directed graph used by biologists to represent the evolutionary history of species whose past includes reticulation events. A phylogenetic network is tree-child if each non-leaf vertex is the parent of a tree vertex or a leaf. Up to a certain equivalence, it has been recently shown that, under two different types of weightings, edge-weighted tree-child networks are determined by their collection of distances between each pair of taxa. However, the size of these collections can be exponential in the size of the taxa set. In this paper, we show that, if we have no "shortcuts", that is, the networks are normal, the same results are obtained with only a quadratic number of inter-taxa distances by using the shortest distance between each pair of taxa. The proofs are constructive and give cubic-time algorithms in the size of the taxa sets for building such weighted networks.

摘要

系统发育网络是一种由生物学家使用的带叶标记、无环、有向图,用于表示过去包含网状事件的物种的进化历史。如果每个非叶顶点是树顶点或叶的父节点,则系统发育网络是树子网络。直到某种等价关系,最近已经表明,在两种不同类型的加权下,边加权树子网络由它们每对分类单元之间的距离集合确定。然而,这些集合的大小可能与分类单元集的大小呈指数关系。在本文中,我们表明,如果没有“捷径”,即网络是正常的,那么通过使用每对分类单元之间的最短距离,仅用二次数量的分类单元间距离就能得到相同的结果。证明是构造性的,并给出了在分类单元集大小方面的立方时间算法来构建这种加权网络。

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