比较和聚合部分解析的树
Comparing and Aggregating Partially Resolved Trees
摘要：
我们定义，分析，并给出有效的算法，两种距离措施的有根和无根的遗传。对于有根树，我们的措施是基于拓扑结构的输入树诱导三胞胎，也就是说，在三个元素的子集的一组物种。对于无根树，测量基于四元组（四元素子集）。基于三元组和四元组的距离提供了树之间相似性的鲁棒且细粒度的度量。相对于传统的四重和三重距离，我们的距离测量的显着特点是它们能够干净地处理未解决的节点的存在，也称为polytomies。对于有根树，这些是有两个以上孩子的节点;对于无根树，它们是度大于三的节点。我们的第一类度量是参数距离，其中有一个参数衡量未解析的三重态/四重态拓扑和解析的拓扑之间的差异。我们的第二类度量是基于Hausdorff距离的。每棵树都被看作是一组所有可能的方法，在这些方法中，树可以被细化以消除未解决的节点。原始（未解析）树之间的距离然后被认为是完全解析树的关联集合之间的豪斯多夫距离，其中集合中的树之间的距离是三元组或四元组距离，视情况而定。
英文摘要：
We define, analyze, and give efficient algorithms for two kinds of distance measures for rooted and unrooted phylogenies. 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 a 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
