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Properties of the generalized Robinson-Foulds metric

机译:广义Robinson-Foulds度量的性质

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Comparing hierarchical structures is a problem with many applications in various fields of biology. In this work we address the problem of comparing phylogenetic trees and quantifying their dissimilarities. The most commonly applied measure of similarity between phylogenetic trees is the Robinson Foulds (RF) metric. The Jaccard-Robinson-Foulds (JRF) metric (of order k) has been recently proposed as a generalization of the RF metric that preserves its widely appreciated properties but increases its resolution and robustness. Here, we conduct thorough experimental analysis of the JRF metric and variations thereof on both real world and simulated data. Our main aim is to deepen the understanding of the properties of this generalized RF metric in comparison to the classical RF metric and other matching based distance measures. To compute the JRF distance between trees, we employ the recently proposed branch-and-cut solver Trajan.
机译:比较层次结构是生物学各个领域中许多应用的问题。在这项工作中,我们解决了比较系统发育树并量化其相似性的问题。系统发育树之间最相似的度量是Robinson Foulds(RF)度量。最近,提出了Jaccard-Robinson-Foulds(JRF)度量(k阶)作为RF度量的一般化,该度量保留了其广泛认可的特性,但提高了其分辨率和鲁棒性。在这里,我们对JRF指标及其在真实世界和模拟数据上的变化进行了全面的实验分析。与经典的RF度量和其他基于匹配的距离度量相比,我们的主要目的是加深对这种广义RF度量的属性的理解。为了计算树之间的JRF距离,我们采用了最近提出的分支切割求解器Trajan。

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