从基因树四重奏识别一级物种网络的可辨识性
Identifiability of Level-1 Species Networks from Gene Tree Quartets
AI总结：
本文研究在网络多物种溯祖模型下，基于四重奏一致性因子识别一级物种网络的拓扑与数值参数的可辨识性，揭示了与3-环相关的若干不可辨识情形。
摘要：
当杂交或其他形式的横向基因转移发生时，物种的进化关系用系统发育网络比用树能更好地表示。虽然此类网络的推断仍然具有挑战性，但最近提出的几种方法都基于四重奏一致性因子——即从物种中采样的一个基因所关联的树展示可能的4分类单元关系的概率。在早期结果的基础上，我们研究了在网络多物种溯祖模型下，哪些一级网络特征可以从一致性因子中被识别。我们获得了关于网络拓扑特征和数值参数的结果，揭示了与网络中3-环相关的一些可辨识性失效情形。
英文摘要：
When hybridization or other forms of lateral gene transfer have occurred, evolutionary relationships of species are better represented by phylogenetic networks than by trees. While inference of such networks remains challenging, several recently proposed methods are based on quartet concordance factors -- the probabilities that a tree relating a gene sampled from the species displays the possible 4-taxon relationships. Building on earlier results, we investigate what level-1 network features are identifiable from concordance factors under the network multispecies coalescent model. We obtain results on both topological features of the network, and numerical parameters, uncovering a number of failures of identifiability related to 3-cycles in the network.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
