{"title":"Clustering systems of phylogenetic networks.","authors":"Marc Hellmuth, David Schaller, Peter F Stadler","doi":"10.1007/s12064-023-00398-w","DOIUrl":null,"url":null,"abstract":"<p><p>Rooted acyclic graphs appear naturally when the phylogenetic relationship of a set X of taxa involves not only speciations but also recombination, horizontal transfer, or hybridization that cannot be captured by trees. A variety of classes of such networks have been discussed in the literature, including phylogenetic, level-1, tree-child, tree-based, galled tree, regular, or normal networks as models of different types of evolutionary processes. Clusters arise in models of phylogeny as the sets [Formula: see text] of descendant taxa of a vertex v. The clustering system [Formula: see text] comprising the clusters of a network N conveys key information on N itself. In the special case of rooted phylogenetic trees, T is uniquely determined by its clustering system [Formula: see text]. Although this is no longer true for networks in general, it is of interest to relate properties of N and [Formula: see text]. Here, we systematically investigate the relationships of several well-studied classes of networks and their clustering systems. The main results are correspondences of classes of networks and clustering systems of the following form: If N is a network of type [Formula: see text], then [Formula: see text] satisfies [Formula: see text], and conversely if [Formula: see text] is a clustering system satisfying [Formula: see text] then there is network N of type [Formula: see text] such that [Formula: see text].This, in turn, allows us to investigate the mutual dependencies between the distinct types of networks in much detail.</p>","PeriodicalId":54428,"journal":{"name":"Theory in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564800/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory in Biosciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s12064-023-00398-w","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/8/12 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
Rooted acyclic graphs appear naturally when the phylogenetic relationship of a set X of taxa involves not only speciations but also recombination, horizontal transfer, or hybridization that cannot be captured by trees. A variety of classes of such networks have been discussed in the literature, including phylogenetic, level-1, tree-child, tree-based, galled tree, regular, or normal networks as models of different types of evolutionary processes. Clusters arise in models of phylogeny as the sets [Formula: see text] of descendant taxa of a vertex v. The clustering system [Formula: see text] comprising the clusters of a network N conveys key information on N itself. In the special case of rooted phylogenetic trees, T is uniquely determined by its clustering system [Formula: see text]. Although this is no longer true for networks in general, it is of interest to relate properties of N and [Formula: see text]. Here, we systematically investigate the relationships of several well-studied classes of networks and their clustering systems. The main results are correspondences of classes of networks and clustering systems of the following form: If N is a network of type [Formula: see text], then [Formula: see text] satisfies [Formula: see text], and conversely if [Formula: see text] is a clustering system satisfying [Formula: see text] then there is network N of type [Formula: see text] such that [Formula: see text].This, in turn, allows us to investigate the mutual dependencies between the distinct types of networks in much detail.
期刊介绍:
Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are:
Artificial Life;
Bioinformatics with a focus on novel methods, phenomena, and interpretations;
Bioinspired Modeling;
Complexity, Robustness, and Resilience;
Embodied Cognition;
Evolutionary Biology;
Evo-Devo;
Game Theoretic Modeling;
Genetics;
History of Biology;
Language Evolution;
Mathematical Biology;
Origin of Life;
Philosophy of Biology;
Population Biology;
Systems Biology;
Theoretical Ecology;
Theoretical Molecular Biology;
Theoretical Neuroscience & Cognition.