Order-Dependent dissimilarity measures on phylogenetic trees.

IF 2.3 4区 数学 Q2 BIOLOGY
Simone Linz, Katherine St John, Charles Semple, Kristina Wicke
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引用次数: 0

Abstract

Ordered leaf attachment, Phylo2Vec, and HOP are three recently introduced vector representations for rooted phylogenetic trees where the representation is determined by an ordering of the underlying leaf set X. Comparing the vectors of two rooted phylogenetic X-trees T and T ' for a fixed ordering on X leads to polynomial-time computable measure for the dissimilarity of T and T ' , albeit dependent on the choice of the leaf ordering. For each of ordered leaf attachment, Phylo2Vec, and HOP, we compare this measure with the rooted subtree prune and regraft distance (rSPR), the hybrid number, and the temporal tree-child hybrid number of T and T ' . Although there is no direct relationship between rSPR and any of the three vector-based measures, we show that, when minimized over all orderings, the hybrid number is equal to HOP and is an upper bound on the other two. Moreover, when minimized over all orderings induced by common cherry-picking sequences of T and T ' , the temporal tree-child hybrid number of T and T ' is equal to each of the three vector-based measures.

系统发育树的序相关不相似性测度。
有序叶片附着、Phylo2Vec和HOP是最近引入的三种根系统发育树的向量表示,其中表示由底层叶集X的顺序决定。比较两个根系统发育X树T和T ‘的向量在X上的固定顺序导致对T和T ’的不相似性的多项式时间可计算度量,尽管依赖于叶片顺序的选择。对于每一个有序叶片附着、Phylo2Vec和HOP,我们将这一度量与T和T '的根子树剪枝和再嫁接距离(rSPR)、杂交数和时间子杂交数进行比较。尽管rSPR与这三种基于向量的度量中的任何一种之间没有直接关系,但我们证明,当在所有排序上最小化时,混合数等于HOP,并且是其他两个的上界。此外,当对常见的樱桃采摘序列T和T ‘引起的所有排序进行最小化时,T和T ’的时间树子杂交数等于三个基于向量的度量中的每一个。
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
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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