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对系统发生网络的软布线简约得分进行限定。

Bounding the Softwired Parsimony Score of a Phylogenetic Network.

机构信息

School of Computer Science, University of Auckland, Auckland, New Zealand.

Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, USA.

出版信息

Bull Math Biol. 2024 Aug 22;86(10):121. doi: 10.1007/s11538-024-01350-9.

Abstract

In comparison to phylogenetic trees, phylogenetic networks are more suitable to represent complex evolutionary histories of species whose past includes reticulation such as hybridisation or lateral gene transfer. However, the reconstruction of phylogenetic networks remains challenging and computationally expensive due to their intricate structural properties. For example, the small parsimony problem that is solvable in polynomial time for phylogenetic trees, becomes NP-hard on phylogenetic networks under softwired and parental parsimony, even for a single binary character and structurally constrained networks. To calculate the parsimony score of a phylogenetic network N, these two parsimony notions consider different exponential-size sets of phylogenetic trees that can be extracted from N and infer the minimum parsimony score over all trees in the set. In this paper, we ask: What is the maximum difference between the parsimony score of any phylogenetic tree that is contained in the set of considered trees and a phylogenetic tree whose parsimony score equates to the parsimony score of N? Given a gap-free sequence alignment of multi-state characters and a rooted binary level-k phylogenetic network, we use the novel concept of an informative blob to show that this difference is bounded by times the softwired parsimony score of N. In particular, the difference is independent of the alignment length and the number of character states. We show that an analogous bound can be obtained for the softwired parsimony score of semi-directed networks, while under parental parsimony on the other hand, such a bound does not hold.

摘要

与系统发生树相比,系统发生网络更适合表示过去经历过网状进化历史的物种的复杂进化史,例如杂交或侧向基因转移。然而,由于其复杂的结构特性,系统发生网络的重建仍然具有挑战性和计算成本高。例如,对于系统发生树来说是可在多项式时间内解决的简约性问题,在软连接和双亲简约性下对于系统发生网络成为 NP 难问题,即使对于单个二元字符和结构受限网络也是如此。为了计算系统发生网络 N 的简约得分,这两种简约概念考虑了从 N 中提取的不同指数大小的系统发生树集合,并推断出集合中所有树的最小简约得分。在本文中,我们提出了以下问题:在考虑的树集合中包含的任何系统发生树的简约得分与简约得分等于 N 的系统发生树的简约得分之间的最大差异是多少?给定多状态字符的无间隙序列比对和有根二元级 k 系统发生网络,我们使用新颖的信息块概念来表明,这个差异被 N 的软连接简约得分的 倍所限制。特别是,该差异与比对长度和字符状态数无关。我们表明,类似的界限也可以应用于半导向网络的软连接简约得分,而在另一方面,对于双亲简约性,这种界限并不成立。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e0/11341636/e79fd6871b8b/11538_2024_1350_Fig1_HTML.jpg

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