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A topological transformation in evolutionary tree search methods based on maximum likelihood combining p-ECR and neighbor joining

机译:基于最大似然结合p-ECR和邻居加入的进化树搜索方法中的拓扑变换

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摘要

BackgroundInference of evolutionary trees using the maximum likelihood principle is NP-hard. Therefore, all practical methods rely on heuristics. The topological transformations often used in heuristics are Nearest Neighbor Interchange (NNI), Subtree Prune and Regraft (SPR) and Tree Bisection and Reconnection (TBR). However, these topological transformations often fall easily into local optima, since there are not many trees accessible in one step from any given tree. Another more exhaustive topological transformation is p-Edge Contraction and Refinement (p-ECR). However, due to its high computation complexity, p-ECR has rarely been used in practice.
机译:背景使用最大似然原理的进化树推断是NP-hard。因此,所有实际方法都依赖于启发式方法。启发式中经常使用的拓扑转换是最近邻居交换(NNI),子树修剪和移植(SPR)和树二等分和重新连接(TBR)。但是,由于从任何给定树到一步之遥的树都不多,因此这些拓扑转换通常容易陷入局部最优。另一个更详尽的拓扑转换是p边缘收缩和细化(p-ECR)。然而,由于其高计算复杂性,在实践中很少使用p-ECR。

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