The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the minimum phylogenetic network problem, in which phylogenetic trees are first inferred, and then the smallest phylogenetic network that displays all the trees is computed. The approach takes advantage of the fact that the theory of phylogenetic trees is mature, and there are excellent tools available for inferring phylogenetic trees from a large number of biomolecular sequences. A tree–child network is a phylogenetic network satisfying the condition that every nonleaf node has at least one child that is of indegree one. Here, we develop a new method that infers the minimum tree–child network by aligning lineage taxon strings in the phylogenetic trees. This algorithmic innovation enables us to get around the limitations of the existing programs for phylogenetic network inference. Our new program, named ALTS, is fast enough to infer a tree–child network with a large number of reticulations for a set of up to 50 phylogenetic trees with 50 taxa that have only trivial common clusters in about a quarter of an hour on average.

中文翻译：

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一种通过对齐谱系分类字符串从树推断系统发育网络的快速且可扩展的方法

系统发育网络的重建是系统发育和基因组进化中一个重要但具有挑战性的问题，因为系统发育网络的空间巨大且无法很好地采样。解决该问题的一种方法是解决最小系统发育网络问题，其中首先推断系统发育树，然后计算显示所有树的最小系统发育网络。该方法利用了系统发育树理论已经成熟的事实，并且有优秀的工具可用于从大量生物分子序列推断系统发育树。树子网络是一种系统发生网络，满足每个非叶节点至少有一个入度为 1 的子节点的条件。在这里，我们开发了一种新方法，通过对齐系统发育树中的谱系分类单元字符串来推断最小树子网络。这种算法创新使我们能够克服现有系统发育网络推理程序的局限性。我们的新程序，名为 ALTS，速度足够快，可以平均在大约一刻钟内推断出具有大量网状结构的树-子网络，该网络包含多达 50 个系统发育树和 50 个类群，这些树只有微不足道的共同簇。