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Computing the Diameter of the Space of Maximum Parsimony Reconciliations in the Duplication-Transfer-Loss Model

机译:在复制-转移-损失模型中计算最大简约对帐的空间直径

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摘要

Phylogenetic tree reconciliation is widely used in the fields of molecular evolution, cophylogenetics, parasitology, and biogeography to study the evolutionary histories of pairs of entities. In these contexts, reconciliation is often performed using maximum parsimony under the Duplication-Transfer-Loss (DTL) event model. In general, the number of maximum parsimony reconciliations (MPRs) can grow exponentially with the size of the trees. While a number of previous efforts have been made to count the number of MPRs, find representative MPRs, and compute the frequencies of events across the space of MPRs, little is known about the structure of MPR space. In particular, how different are MPRs in terms of the events that they comprise? One way to address this question is to compute the diameter of MPR space, defined to be the maximum number of DTL events that distinguish any two MPRs in the solution space. We show how to compute the diameter of MPR space in polynomial time and then apply this algorithm to a large biological dataset to study the variability of events.
机译:系统发育树和解广泛用于分子进化,系统发生学,寄生虫学和生物地理学领域,以研究实体对的进化历史。在这些情况下,对帐通常在复制-传输-丢失(DTL)事件模型下使用最大简约性进行。通常,最大简约对帐(MPR)的数量可以随树的大小呈指数增长。尽管已经进行了许多先前的努力来计算MPR的数量,找到代表性的MPR并计算跨MPR空间的事件的频率,但对MPR空间的结构知之甚少。特别是,MPR包含的事件有何不同?解决此问题的一种方法是计算MPR空间的直径,定义为区分解决方案空间中任意两个MPR的DTL事件的最大数量。我们展示了如何在多项式时间内计算MPR空间的直径,然后将该算法应用于大型生物数据集以研究事件的可变性。

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