NeighborNet:改进的算法和实现。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Frontiers in bioinformatics Pub Date : 2023-09-20 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1178600
David Bryant, Daniel H Huson
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引用次数: 0

摘要

NeighborNet构建系统发育网络以可视化距离数据。这是一种广泛应用的流行方法。虽然一些研究已经调查了它的数学特征,但这里我们关注的是计算方面。该算法分为三个步骤。我们提出了第一步的一个新的简化公式,旨在计算循环排序。我们提供了第二步的第一个技术描述,即分割权重的估计。我们通过构建和绘制网络来回顾第三步。最后,我们讨论了如何最好地解释网络,回顾了相关的方法,并提出了一些悬而未决的问题。
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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NeighborNet: improved algorithms and implementation.

NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions.

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