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Comparing and Aggregating Partially Resolved Trees

机译:比较和聚合部分解析的树

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We define, analyze, and give efficient algorithms for two kinds of distance measures for rooted and unrooted phytogenies. For rooted trees, our measures are based on the topologies the input trees induce on triplets; that is, on three-element subsets of the set of species. For unrooted trees, the measures are based on quartets (four-element subsets). Triplet and quartet-based distances provide a robust and fine-grained measure of the similarities between trees. The distinguishing feature of our distance measures relative to traditional quartet and triplet distances is their ability to deal cleanly with the presence of unresolved nodes, also called polytomies. For rooted trees, these are nodes with more than two children; for unrooted trees, they are nodes of degree greater than three. Our first class of measures are parametric distances, where there is parameter that weighs the difference between an unresolved triplet/quartet topology and a resolved one. Our second class of measures are based on Hausdorff distance. Each tree is viewed as a set of all possible ways in which the tree could be refined to eliminate unresolved nodes. The distance between the original (unresolved) trees is then taken to be the Hausdorff distance between the associated sets of fully resolved trees, where the distance between trees in the sets is the triplet or quartet distance, as appropriate.
机译:我们为有根和无根植物遗传学的两种距离量度定义,分析并给出有效的算法。对于有根的树,我们的度量基于输入树在三联体上诱导的拓扑。也就是说,在一组物种的三元素子集上。对于无根树木,这些措施基于四重奏(四元素子集)。基于三重态和四重态的距离为树木之间的相似性提供了鲁棒且细粒度的度量。相对于传统四重奏和三重奏距离,我们的距离度量的显着特征是它们能够很好地处理未解决的结点(也称为多义词)的处理能力。对于有根的树,这些是具有两个以上子节点的节点。对于无根树木,它们是度数大于3的节点。我们的第一类度量是参数距离,其中的参数权衡了未解析的三重态/四重态拓扑和已解析的三重态/四重态拓扑之间的差异。我们的第二类量度基于Hausdorff距离。每棵树被视为一组所有可能的方法,可以通过这些方法来精炼树以消除未解析的节点。然后,将原始(未解析)树之间的距离作为关联的完全解析树集之间的Hausdorff距离,其中,树中的树之间的距离视情况为三重态或四重态距离。

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