On the existence of funneled orientations for classes of rooted phylogenetic networks

IF 0.9 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
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引用次数: 0

Abstract

Recently, there has been a growing interest in the relationships between unrooted and rooted phylogenetic networks. In this context, a natural question to ask is if an unrooted phylogenetic network U can be oriented as a rooted phylogenetic network such that the latter satisfies certain structural properties. In a recent preprint, Bulteau et al. claim that it is NP-hard to decide if U has a funneled (resp. funneled tree-child) orientation, for when the internal vertices of U have degree at most 5. Unfortunately, the proof of their funneled tree-child result appears to be incorrect. In this paper, we show that, despite their incorrect proof, it is NP-hard to decide if U has a funneled tree-child orientation even if each internal vertex has degree 5 and that NP-hardness remains for other popular classes of rooted phylogenetic networks such as funneled normal and funneled reticulation-visible. Additionally, our results hold regardless of whether U is rooted at an existing vertex or by subdividing an edge with the root.
论有根系统发育网络的漏斗方向的存在性
最近,人们对无根系统发育网络和有根系统发育网络之间的关系越来越感兴趣。在这种情况下,一个自然而然的问题是,无根系统发育网络 U 是否可以定向为有根系统发育网络,从而使后者满足某些结构特性。在最近的预印本中,Bulteau 等人声称,当 U 的内部顶点阶数最多为 5 时,判断 U 是否具有漏斗状(或漏斗状树子)定向是 NP 难的。遗憾的是,他们对漏斗树子结果的证明似乎并不正确。在本文中,我们证明了尽管他们的证明不正确,但即使每个内部顶点的阶数都是 5,要判断 U 是否具有漏斗树子方向也是 NP-困难的,而且对于其他流行的有根系统发育网络类别,如漏斗正常和漏斗网状可见,NP-困难性依然存在。此外,无论 U 是根植于现有顶点还是通过细分根边,我们的结果都是成立的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Theoretical Computer Science
Theoretical Computer Science 工程技术-计算机:理论方法
CiteScore
2.60
自引率
18.20%
发文量
471
审稿时长
12.6 months
期刊介绍: Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computation and, as a consequence of this understanding, provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing.
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