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A fundamental problem in the study of phylogenetic networks is to determine whether or not a given phylogenetic network contains a given phylogenetic tree. We develop a quadratic-time algorithm for this problem for binary nearly-stable…

Data Structures and Algorithms · Computer Science 2022-08-29 Philippe Gambette , Andreas D. M. Gunawan , Anthony Labarre , Stéphane Vialette , Louxin Zhang

Many biological studies involve inferring the evolutionary history of a sample of individuals from a large population and interpreting the reconstructed tree. Such an ascertained tree typically represents only a small part of a…

Populations and Evolution · Quantitative Biology 2024-08-13 Michael Celentano , William S. DeWitt , Sebastian Prillo , Yun S. Song

We present an efficient phylogenetic reconstruction algorithm allowing insertions and deletions which provably achieves a sequence-length requirement (or sample complexity) growing polynomially in the number of taxa. Our algorithm is…

Probability · Mathematics 2013-02-25 Constantinos Daskalakis , Sebastien Roch

Here we present a new fixed parameter tractable algorithm to compute the hybridization number r of two rooted, not necessarily binary phylogenetic trees on taxon set X in time (6^r.r!).poly(n)$, where n=|X|. The novelty of this approach is…

Quantitative Methods · Quantitative Biology 2012-07-26 Teresa Piovesan , Steven Kelk

Phylogenetic networks are a generalization of evolutionary trees that are used by biologists to represent the evolution of organisms which have undergone reticulate evolution. Essentially, a phylogenetic network is a directed acyclic graph…

Populations and Evolution · Quantitative Biology 2017-02-01 Leo van Iersel , Vincent Moulton , Eveline de Swart , Taoyang Wu

Estimating phylogenetic trees is an important problem in evolutionary biology, environmental policy and medicine. Although trees are estimated, their uncertainties are discarded by mathematicians working in tree space. Here we explicitly…

Methodology · Statistics 2017-10-16 Amy D. Willis , Rayna C. Bell

Optimization for deep networks is currently a very active area of research. As neural networks become deeper, the ability in manually optimizing the network becomes harder. Mini-batch normalization, identification of effective respective…

Neural and Evolutionary Computing · Computer Science 2018-08-07 M. U. B. Dias , D. D. N. De Silva , S. Fernando

We consider the problem of estimating the evolutionary history of a set of species (phylogeny or species tree) from several genes. It is known that the evolutionary history of individual genes (gene trees) might be topologically distinct…

Populations and Evolution · Quantitative Biology 2016-11-18 Gautam Dasarathy , Robert Nowak , Sebastien Roch

Background: The reconstruction of the phylogenetic tree topology of four taxa is, still nowadays, one of the main challenges in phylogenetics. Its difficulties lie in considering not too restrictive evolutionary models, and correctly…

Populations and Evolution · Quantitative Biology 2014-06-19 Esther Ibáñez , Marta Casanellas

In this study, we investigate the problem of comparing gene trees reconciled with the same species tree using a novel semi-metric, called the Path-Label Reconciliation (PLR) dissimilarity measure. This approach not only quantifies…

A phylogenetic tree is an important way in Bioinformatics to find the evolutionary relationship among biological species. In this research, a proposed model is described for the estimation of a phylogenetic tree for a given set of data. To…

Populations and Evolution · Quantitative Biology 2025-09-03 S M Rafiuddin

Since the advent of modern bioinformatics, the challenging, multifaceted problem of reconstructing phylogenetic history from biological sequences has hatched perennial statistical and algorithmic innovation. Studies of the phylogenetic…

Data Structures and Algorithms · Computer Science 2024-03-05 Matthew Andres Moreno , Santiago Rodriguez Papa , Emily Dolson

Neural Networks and Decision Trees: two popular techniques for supervised learning that are seemingly disconnected in their formulation and optimization method, have recently been combined in a single construct. The connection pivots on…

Machine Learning · Statistics 2020-02-27 Giuseppe Nuti , Lluís Antoni Jiménez Rugama , Kaspar Thommen

An important problem in phylogenetics is the construction of phylogenetic trees. One way to approach this problem, known as the supertree method, involves inferring a phylogenetic tree with leaves consisting of a set $X$ of species from a…

Populations and Evolution · Quantitative Biology 2017-11-21 Katharine T. Huber , Vincent Moulton , Charles Semple , Taoyang Wu

The ancestral maximum-likelihood and phylogeography problems are two fundamental problems involving evolutionary studies. The ancestral maximum-likelihood problem involves identifying a rooted tree alongside internal node sequences that…

Data Structures and Algorithms · Computer Science 2023-08-15 Mohammad-Hadi Foroughmand-Araabi , Sama Goliaei , Kasra Alishahi

A model of genomic sequence evolution on a species tree should include not only a sequence substitution process, but also a coalescent process, since different sites may evolve on different gene trees due to incomplete lineage sorting.…

Populations and Evolution · Quantitative Biology 2023-03-15 Elizabeth A. Allman , Colby Long , John A. Rhodes

Computational approaches in historical linguistics have been increasingly applied during the past decade and many new methods that implement parts of the traditional comparative method have been proposed. Despite these increased efforts,…

Computation and Language · Computer Science 2022-04-12 Johann-Mattis List , Robert Forkel , Nathan W. Hill

Probability estimation of tree topologies is one of the fundamental tasks in phylogenetic inference. The recently proposed subsplit Bayesian networks (SBNs) provide a powerful probabilistic graphical model for tree topology probability…

Populations and Evolution · Quantitative Biology 2024-09-10 Tianyu Xie , Musu Yuan , Minghua Deng , Cheng Zhang

Optimizing a neural network's performance is a tedious and time taking process, this iterative process does not have any defined solution which can work for all the problems. Optimization can be roughly categorized into - Architecture and…

Machine Learning · Computer Science 2019-12-16 Siddhartha Dhar Choudhury , Shashank Pandey , Kunal Mehrotra

We propose a tree regularization framework, which enables many tree models to perform feature selection efficiently. The key idea of the regularization framework is to penalize selecting a new feature for splitting when its gain (e.g.…

Machine Learning · Computer Science 2012-03-22 Houtao Deng , George Runger