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Constructing a Smallest Refining Galled Phylogenetic Network

机译:构建最小的精炼薄膜发育网络

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Reticulation events occur frequently in many types of species. Therefore, to develop accurate methods for reconstructing phylogenetic networks in order to describe evolutionary history in the presence of reticulation events is important. Previous work has suggested that constructing phylogenetic networks by merging gene trees is a biologically meaningful approach. This paper presents two new efficient algorithms for inferring a phylogenetic network from a set T of gene trees of arbitrary degrees. The first algorithm solves the open problem of constructing a refining galled network for T (if one exists) with no restriction on the number of hybrid nodes; in fact, it outputs the smallest possible solution. In comparison, the previously best method (SpNet) can only construct networks having a single hybrid node. For cases where there exists no refining galled network for T, our second algorithm identifies a minimum subset of the species set to be removed so that the resulting trees can be combined into a galled network. Based on our two algorithms, we propose two general methods named RGNet and RGNet+. Through simulations, we show that our methods outperform the other existing methods neighbor-joining, NeighborNet, and SpNet.
机译:网状化事件经常发生在许多类型的物种中。因此,为了制定重建系统发育网络的准确方法,以便在网状化事件存在下描述进化历史很重要。以前的工作表明,通过合并基因树构建系统发育网络是一种生物学上有意义的方法。本文提出了两种新的高效算法,用于从任意度的基因树中推断系统发育网络。第一算法解决了构建用于T(如果存在的炼油网络的打开问题,对混合节点的数量没有限制;实际上,它输出了最小的解决方案。相比之下,先前最好的方法(SPNET)只能构建具有单个混合节点的网络。对于没有用于T的炼油网的情况,我们的第二算法识别要删除的物种的最小子集,使得得到的树可以组合成隐形网络。基于我们的两个算法,我们提出了两个名为RGNET和RGNET +的一般方法。通过仿真,我们表明我们的方法优于其他现有方法邻居加入,邻居和Spnet。

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