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Comparing and aggregating partially resolved trees

机译:比较和汇总部分解析的树

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Partially-resolved - that is, non-binary - trees arise frequently in the analysis of species evolution. Non-binary nodes, also called multifurcations, must be treated carefully, since they can be interpreted as reflecting either lack of information or actual evolutionary history. While several distance measures exist for comparing trees, none of them deal explicitly with this dichotomy. Here we introduce two kinds of distance measures between rooted and unrooted partially-resolved phylogenetic trees over the same set of species; the measures address multifurcations directly. For rooted trees, the 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). The 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. The second class of measures are based on the Hausdorff distance, where each tree is viewed as a set of all possible ways in which the tree can be refined to eliminate unresolved nodes. We give efficient algorithms for computing parametric distances and give conditions under which Hausdorff distances can be calculated approximately in polynomial time. Additionally, we (i) derive the expected value of the parametric distance between two random trees, (ii) characterize the conditions under which parametric distances are near-metrics or metrics, (iii) study the computational and algorithmic properties of consensus tree methods based on the measures, and (iv) analyze the interrelationships among Hausdorff and parametric distances.
机译:在物种进化分析中,部分分解的树木(即非二叉树)经常出现。非二进制节点(也称为多分支)必须谨慎对待,因为它们可以解释为反映信息不足或实际的进化历史。尽管存在几种用于比较树木的距离度量,但没有一个度量明确地处理这种二分法。在这里,我们介绍了在同一物种上有根的和无根的部分分解的系统发育树之间的两种距离度量;这些措施直接解决了分支问题。对于有根的树,这些度量基于输入树在三联体上诱导的拓扑;也就是物种集合的三元素子集。对于无根树木,这些措施基于四重奏(四元素子集)。第一类度量是参数距离,其中存在一个参数,用于权衡未解析的三重态/四重态拓扑和已解析的三重态/四重态拓扑之间的差异。第二类度量是基于Hausdorff距离的,其中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。我们给出了用于计算参数距离的有效算法,并给出了可以在多项式时间内近似计算Hausdorff距离的条件。此外,我们(i)得出两棵随机树之间参数距离的期望值,(ii)表征参数距离是接近度量或度量的条件,(iii)研究基于共识树方法的计算和算法性质(四)分析Hausdorff与参数距离之间的相互关系。

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