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Weighted recursive trees are built by adding successively vertices with predetermined weights to a tree: each new vertex is attached to a parent chosen randomly proportionally to its weight. Under some assumptions on the sequence of…

Probability · Mathematics 2021-12-16 Michel Pain , Delphin Sénizergues

Using topological summaries of gene trees as a basis for species tree inference is a promising approach to obtain acceptable speed on genomic-scale datasets, and to avoid some undesirable modeling assumptions. Here we study the…

Populations and Evolution · Quantitative Biology 2017-04-17 Elizabeth S. Allman , James H. Degnan , John A. Rhodes

Comparing and computing distances between phylogenetic trees are important biological problems, especially for models where edge lengths play an important role. The geodesic distance measure between two phylogenetic trees with edge lengths…

Populations and Evolution · Quantitative Biology 2009-11-05 Megan Owen , J. Scott Provan

In this paper, we consider a tree inference problem motivated by the critical problem in single-cell genomics of reconstructing dynamic cellular processes from sequencing data. In particular, given a population of cells sampled from such a…

Methodology · Statistics 2025-07-16 Elodie Maignant , Tim Conrad , Christoph von Tycowicz

For a model of molecular evolution to be useful for phylogenetic inference, the topology of evolutionary trees must be identifiable. That is, from a joint distribution the model predicts, it must be possible to recover the tree parameter.…

Populations and Evolution · Quantitative Biology 2011-11-09 Elizabeth S. Allman , John A. Rhodes

Inference of species networks from genomic data under the Network Multispecies Coalescent Model is currently severely limited by heavy computational demands. It also remains unclear how complicated networks can be for consistent inference…

Populations and Evolution · Quantitative Biology 2022-05-10 Elizabeth S. Allman , Hector Baños , Jonathan D. Mitchell , John A. Rhodes

Phylogenetic tree shapes capture fundamental signatures of evolution. We consider ``ranked'' tree shapes, which are equipped with a total order on the internal nodes compatible with the tree graph. Recent work has established an elegant…

Populations and Evolution · Quantitative Biology 2026-03-10 Chris Jennings-Shaffer , Ziyue , Chen , Julia A Palacios , Frederick A Matsen

In evolutionary studies it is common to use phylogenetic trees to represent the evolutionary history of a set of species. However, in case the transfer of genes or other genetic information between the species or their ancestors has…

Combinatorics · Mathematics 2022-02-15 Katharina T. Huber , Vincent Moulton , Guillaume E. Scholz

Metric embedding has become a common technique in the design of algorithms. Its applicability is often dependent on how high the embedding's distortion is. For example, embedding finite metric space into trees may require linear distortion…

Data Structures and Algorithms · Computer Science 2007-05-23 Yair Bartal , Manor Mendel

We consider growing random recursive trees in random environment, in which at each step a new vertex is attached (by an edge of a random length) to an existing tree vertex according to a probability distribution that assigns the tree…

Probability · Mathematics 2007-05-23 Konstantin Borovkov , Vladimir Vatutin

Recently it was shown that, if the subtree and chain reduction rules have been applied exhaustively to two unrooted phylogenetic trees, the reduced trees will have at most 15k-9 taxa where k is the TBR (Tree Bisection and Reconnection)…

Data Structures and Algorithms · Computer Science 2021-04-13 Steven Kelk , Simone Linz

The number of the non-shared edges of two phylogenies is a basic measure of the dissimilarity between the phylogenies. The non-shared edges are also the building block for approximating a more sophisticated metric called the nearest…

Data Structures and Algorithms · Computer Science 2007-05-23 Wing-Kai Hon , Ming-Yang Kao , Tak-Wah Lam , Wing-Kin Sung , Siu-Ming Yiu

We analyse a maximum-likelihood approach for combining phylogenetic trees into a larger `supertree'. This is based on a simple exponential model of phylogenetic error, which ensures that ML supertrees have a simple combinatorial description…

Populations and Evolution · Quantitative Biology 2007-08-17 Mike Steel , Allen Rodrigo

The mutational heterogeneity of tumours can be described with a tree representing the evolutionary history of the tumour. With noisy sequencing data there may be uncertainty in the inferred tree structure, while we may also wish to study…

Computational Complexity · Computer Science 2025-01-14 Luís Cunha , Jack Kuipers , Thiago Lopes

Quartet Reconstruction, the task of recovering a phylogenetic tree from smaller trees on four species called \textit{quartets}, is a well-studied problem in theoretical computer science with far-reaching connections to statistics, graph…

Data Structures and Algorithms · Computer Science 2026-04-21 Dionysis Arvanitakis , Vaggos Chatziafratis , Yiyuan Luo , Konstantin Makarychev

Reconstructing the tree of life from molecular sequences is a fundamental problem in computational biology. Modern data sets often contain a large number of genes, which can complicate the reconstruction problem due to the fact that…

Probability · Mathematics 2017-07-21 Constantinos Daskalakis , Sebastien Roch

The presence of reticulate evolutionary events in phylogenies turn phylogenetic trees into phylogenetic networks. These events imply in particular that there may exist multiple evolutionary paths from a non-extant species to an extant one,…

Populations and Evolution · Quantitative Biology 2008-03-21 Gabriel Cardona , Merce Llabres , Francesc Rossello , Gabriel Valiente

Distance-based approaches in phylogenetics such as Neighbor-Joining are a fast and popular approach for building trees. These methods take pairs of sequences from them construct a value that, in expectation, is additive under a stochastic…

Populations and Evolution · Quantitative Biology 2008-08-21 Mike Steel

Distances are pervasive in machine learning. They serve as similarity measures, loss functions, and learning targets; it is said that a good distance measure solves a task. When defining distances, the triangle inequality has proven to be a…

Machine Learning · Computer Science 2020-07-08 Silviu Pitis , Harris Chan , Kiarash Jamali , Jimmy Ba

Dynamic trees are mixtures of tree structured belief networks. They solve some of the problems of fixed tree networks at the cost of making exact inference intractable. For this reason approximate methods such as sampling or mean field…

Machine Learning · Computer Science 2013-01-18 Amos J. Storkey
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