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Rooted phylogenetic networks provide a more complete representation of the ancestral relationship between species than phylogenetic trees when reticulate evolutionary processes are at play. One way to reconstruct a phylogenetic network is…

Combinatorics · Mathematics 2020-12-02 Allan Bai , Peter Erdos , Charles Semple , Mike Steel

The spanning tree heuristic is a commonly adopted procedure in network inference and estimation. It allows one to generalize an inference method developed for trees, which is usually based on a statistically rigorous approach, to a…

Signal Processing · Electrical Eng. & Systems 2019-05-22 Feng Ji , Wenchang Tang , Wee Peng Tay

Bayesian phylogenetic inference is currently done via Markov chain Monte Carlo (MCMC) with simple proposal mechanisms. This hinders exploration efficiency and often requires long runs to deliver accurate posterior estimates. In this paper,…

Machine Learning · Statistics 2024-05-24 Cheng Zhang , Frederick A. Matsen

Phylogenomics is a new field which applies to tools in phylogenetics to genome data. Due to a new technology and increasing amount of data, we face new challenges to analyze them over a space of phylogenetic trees. Because a space of…

Combinatorics · Mathematics 2020-05-15 Ruriko Yoshida

Phylogenetic trees and networks are graphs used to model evolutionary relationships, with trees representing strictly branching histories and networks allowing for events in which lineages merge, called reticulation events. While the…

Populations and Evolution · Quantitative Biology 2026-04-17 Martin Frohn , Niels Holtgrefe , Leo van Iersel , Mark Jones , Steven Kelk

Polyploidization is an evolutionary process by which a species acquires multiple copies of its complete set of chromosomes. The reticulate nature of the signal left behind by it means that phylogenetic networks offer themselves as a…

Populations and Evolution · Quantitative Biology 2023-02-21 Katharina T. Huber , Liam J. Maher

The amount of completely sequenced chloroplast genomes increases rapidly every day, leading to the possibility to build large scale phylogenetic trees of plant species. Considering a subset of close plant species defined according to their…

Artificial Intelligence · Computer Science 2015-04-21 Bassam AlKindy , Christophe Guyeux , Jean-François Couchot , Michel Salomon , Christian Parisod , Jacques M. Bahi

Networks are ubiquitous in biology and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used to complete a partially known network by integrating various…

Machine Learning · Computer Science 2014-04-25 Marie Schrynemackers , Louis Wehenkel , M. Madan Babu , Pierre Geurts

The multispecies coalescent process models the genealogical relationships of genes sampled from several species, enabling useful predictions about phenomena such as the discordance between the gene tree and the species phylogeny due to…

Populations and Evolution · Quantitative Biology 2020-12-11 Jakub Truszkowski , Celine Scornavacca , Fabio Pardi

In evolutionary biology, phylogenetic networks are graphs that provide a flexible framework for representing complex evolutionary histories that involve reticulate evolutionary events. Recently phylogenetic studies have started to focus on…

Populations and Evolution · Quantitative Biology 2025-11-17 Niels Holtgrefe , Katharina T. Huber , Leo van Iersel , Mark Jones , Vincent Moulton

Phylogenetic trees are the fundamental mathematical representation of evolutionary processes in biology. They are also objects of interest in pure mathematics, such as algebraic geometry and combinatorics, due to their discrete geometry.…

Metric Geometry · Mathematics 2022-07-01 Anthea Monod , Bo Lin , Ruriko Yoshida , Qiwen Kang

Bayesian inference methods rely on numerical algorithms for both model selection and parameter inference. In general, these algorithms require a high computational effort to yield reliable estimates. One of the major challenges in…

Quantitative Methods · Quantitative Biology 2018-08-09 Patricio Maturana , Brendon J. Brewer , Steffen Klaere , Remco Bouckaert

Decision trees are widely used for non-linear modeling, as they capture interactions between predictors while producing inherently interpretable models. Despite their popularity, performing inference on the non-linear fit remains largely…

Methodology · Statistics 2026-04-14 Soham Bakshi , Snigdha Panigrahi

Evolutionary histories for species that cross with one another or exchange genetic material can be represented by leaf-labelled, directed graphs called phylogenetic networks. A major challenge in the burgeoning area of phylogenetic networks…

Data Structures and Algorithms · Computer Science 2021-09-24 Leo van Iersel , Sjors Kole , Vincent Moulton , Leonie Nipius

It is challenging to design large and low-cost communication networks. In this paper, we formulate this challenge as the prize-collecting Steiner Tree Problem (PCSTP). The objective is to minimize the costs of transmission routes and the…

Networking and Internet Architecture · Computer Science 2019-02-07 Yahui Sun , Marcus Brazil , Doreen Thomas , Saman Halgamuge

In biodiversity conservation it is often necessary to prioritize the species to conserve. Existing approaches to prioritization, e.g. the Fair Proportion Index and the Shapley Value, are based on phylogenetic trees and rank species…

Populations and Evolution · Quantitative Biology 2018-02-07 Kristina Wicke , Mareike Fischer

Phylogenetic networks are leaf-labelled directed acyclic graphs that are used to describe non-treelike evolutionary histories and are thus a generalization of phylogenetic trees. The hybridization number of a phylogenetic network is the sum…

Data Structures and Algorithms · Computer Science 2016-06-01 Leo van Iersel , Steven Kelk , Nela Lekić , Chris Whidden , Norbert Zeh

Evolutionary relationships between species are usually inferred through phylogenetic analysis, which provides phylogenetic trees computed from allelic profiles built by sequencing specific regions of the sequences and abstracting them to…

Data Structures and Algorithms · Computer Science 2021-01-01 Luana Silva

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

Hierarchical structure is ubiquitous in data across many domains. There are many hierarchical clustering methods, frequently used by domain experts, which strive to discover this structure. However, most of these methods limit discoverable…

Machine Learning · Computer Science 2012-03-19 Charles Blundell , Yee Whye Teh , Katherine A. Heller
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