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Complex systems of polynomial equations have to be set up and solved algebraically in order to obtain analytic solutions for maximum likelihood on phylogenetic trees. This has restricted the types of systems previously resolved to the…

种群与进化 · 定量生物学 2007-05-23 Benny Chor , Michael D. Hendy , Sagi Snir

We prove identifiability of the tree parameters of the 3-class Jukes-Cantor mixture model. The proof uses ideas from algebraic statistics, in particular: finding phylogenetic invariants that separate the varieties associated to different…

种群与进化 · 定量生物学 2014-08-12 Colby Long , Seth Sullivant

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…

数据结构与算法 · 计算机科学 2023-08-15 Mohammad-Hadi Foroughmand-Araabi , Sama Goliaei , Kasra Alishahi

Jukes-Cantor model is one of the most meaningful statistical models from a biological perspective. We are interested in computing the algebraic degrees for phylogenetic varieties, which we call phylogenetic degrees, associated to the…

代数几何 · 数学 2024-05-31 Rodica Andreea Dinu , Martin Vodička

We consider a broadcasting problem on a tree where a binary digit (e.g., a spin or a nucleotide's purine/pyrimidine type) is propagated from the root to the leaves through symmetric noisy channels on the edges that randomly flip the state…

概率论 · 数学 2025-01-24 David Clancy , Hanbaek Lyu , Sebastien Roch , Allan Sly

Reconstructing evolutionary trees from molecular sequence data is a fundamental problem in computational biology. Stochastic models of sequence evolution are closely related to spin systems that have been extensively studied in statistical…

概率论 · 数学 2017-07-20 Sebastien Roch , Allan Sly

We give a greedy learning algorithm for reconstructing an evolutionary tree based on a certain harmonic average on triplets of terminal taxa. After the pairwise distances between terminal taxa are estimated from sequence data, the algorithm…

数据结构与算法 · 计算机科学 2007-05-23 Miklos Csuros , Ming-Yang Kao

We introduce new methods for phylogenetic tree quartet construction by using machine learning to optimize the power of phylogenetic invariants. Phylogenetic invariants are polynomials in the joint probabilities which vanish under a model of…

种群与进化 · 定量生物学 2007-05-23 Nicholas Eriksson , Yuan Yao

The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies…

种群与进化 · 定量生物学 2016-09-07 Marta Casanellas , Mike Steel

Maximum likelihood estimators are used extensively to estimate unknown parameters of stochastic trait evolution models on phylogenetic trees. Although the MLE has been proven to converge to the true value in the independent-sample case, we…

种群与进化 · 定量生物学 2019-11-26 Lam Si Tung Ho , Vu Dinh , Frederick A. Matsen , Marc A. Suchard

As is the case for many curved exponential families, the computation of maximum likelihood estimates in a multivariate normal model with a Kronecker covariance structure is typically carried out with an iterative algorithm, specifically, a…

统计理论 · 数学 2024-08-28 Mathias Drton , Alexandros Grosdos , Andrew McCormack

We investigated testing the likelihood of a phylogenetic tree by comparison to its subtree pruning and regrafting (SPR) neighbors, with or without re-optimizing branch lengths. This is inspired by aspects of Bayesian significance tests, and…

应用统计 · 统计学 2014-07-30 Thurston H. Y. Dang , Elchanan Mossel

A phylogenetic variety is an algebraic variety parameterized by a statistical model of the evolution of biological sequences along a tree. Understanding this variety is an important problem in the area of algebraic statistics with…

种群与进化 · 定量生物学 2024-05-22 Luis David Garcia Puente , Marina Garrote-López , Elima Shehu

Phylogenetic networks provide a means of describing the evolutionary history of sets of species believed to have undergone hybridization or gene flow during their evolution. The mutation process for a set of such species can be modeled as a…

种群与进化 · 定量生物学 2022-11-23 Travis Barton , Elizabeth Gross , Colby Long , Joseph Rusinko

We address phylogenetic reconstruction when the data is generated from a mixture distribution. Such topics have gained considerable attention in the biological community with the clear evidence of heterogeneity of mutation rates. In our…

种群与进化 · 定量生物学 2007-05-23 Daniel Stefankovic , Eric Vigoda

We examine a mathematical question concerning the reconstruction accuracy of the Fitch algorithm for reconstructing the ancestral sequence of the most recent common ancestor given a phylogenetic tree and sequence data for all taxa under…

种群与进化 · 定量生物学 2017-06-20 Lina Herbst , Mareike Fischer

In this paper, we investigate a conjecture by von Haeseler concerning the Maximum Parsimony method for phylogenetic estimation, which was published by the Newton Institute in Cambridge on a list of open phylogenetic problems in 2007. This…

种群与进化 · 定量生物学 2010-07-30 Mareike Fischer

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…

种群与进化 · 定量生物学 2014-06-19 Esther Ibáñez , Marta Casanellas

Phylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees, such as hybridization, introgression, and lateral gene transfer. Studying phylogenetic networks under a statistical model of DNA…

种群与进化 · 定量生物学 2024-07-17 M. Frohn , N. Holtgrefe , L. van Iersel , M. Jones , S. Kelk

CRISPR technology has enabled large-scale cell lineage tracing for complex multicellular organisms by mutating synthetic genomic barcodes during organismal development. However, these sophisticated biological tools currently use ad-hoc and…

定量方法 · 定量生物学 2019-04-02 Jean Feng , William S DeWitt , Aaron McKenna , Noah Simon , Amy Willis , Frederick A Matsen
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