Metrics for classes of semi-binary phylogenetic networks using μ-representations

IF 1.3 3区 数学 Q3 MATHEMATICS, APPLIED
Christopher Reichling, Leo van Iersel, Yukihiro Murakami
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引用次数: 0

Abstract

Phylogenetic networks are useful in representing the evolutionary history of taxa. In certain scenarios, one requires a way to compare different networks. In practice, this can be rather difficult, except within specific classes of networks. In this paper, we derive metrics for the class of orchard networks and the class of strongly reticulation-visible networks, from variants of so-called μ-representations, which are vector representations of networks. For both network classes, we impose degree constraints on the vertices, by considering semi-binary networks.
使用μ表示的半二元系统发育网络类的度量
系统发育网络在描述分类群的进化史方面是有用的。在某些情况下,需要一种比较不同网络的方法。在实践中,这可能相当困难,除非在特定的网络类别中。在本文中,我们从所谓的μ-表示的变体中导出了果园网络类和强网状可见网络类的度量,μ-表示是网络的向量表示。对于这两类网络,我们通过考虑半二元网络对顶点施加度约束。
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来源期刊
Advances in Applied Mathematics
Advances in Applied Mathematics 数学-应用数学
CiteScore
2.00
自引率
9.10%
发文量
88
审稿时长
85 days
期刊介绍: Interdisciplinary in its coverage, Advances in Applied Mathematics is dedicated to the publication of original and survey articles on rigorous methods and results in applied mathematics. The journal features articles on discrete mathematics, discrete probability theory, theoretical statistics, mathematical biology and bioinformatics, applied commutative algebra and algebraic geometry, convexity theory, experimental mathematics, theoretical computer science, and other areas. Emphasizing papers that represent a substantial mathematical advance in their field, the journal is an excellent source of current information for mathematicians, computer scientists, applied mathematicians, physicists, statisticians, and biologists. Over the past ten years, Advances in Applied Mathematics has published research papers written by many of the foremost mathematicians of our time.
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