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Loss tomography has received considerable attention in recent years and a number of estimators based on maximum likelihood (ML) or Bayesian principles have been proposed. Almost all of the estimators are devoted to the tree topology despite…

Networking and Internet Architecture · Computer Science 2015-03-19 Weiping Zhu , Ke Deng

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

Probabilistic Latent Tensor Factorization (PLTF) is a recently proposed probabilistic framework for modelling multi-way data. Not only the common tensor factorization models but also any arbitrary tensor factorization structure can be…

Computation · Statistics 2014-09-30 Beyza Ermis , Y. Kenan Yılmaz , A. Taylan Cemgil , Evrim Acar

The aim of this review is to present and analyze the probabilistic models of mathematical phylogenetics which have been intensively used in recent years in biology as the cornerstone of attempts to infer and reconstruct the ancestral…

Populations and Evolution · Quantitative Biology 2020-01-08 Peter D Jarvis , Jeremy G Sumner

This paper concerns the use of the expectation-maximisation (EM) algorithm for inference in partially observed diffusion processes. In this context, a well known problem is that all except a few diffusion processes lack closed-form…

Statistics Theory · Mathematics 2010-08-18 Jimmy Olsson , Jonas Ströjby

Gene gain-loss-duplication models are commonly based on continuous-time birth-death processes. Employed in a phylogenetic context, such models have been increasingly popular in studies of gene content evolution across multiple genomes.…

Populations and Evolution · Quantitative Biology 2021-07-27 Miklos Csuros

Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in…

Machine Learning · Computer Science 2024-09-10 Martin Roa-Villescas , Xuanzhao Gao , Sander Stuijk , Henk Corporaal , Jin-Guo Liu

We study the problem of model selection type aggregation with respect to the Kullback-Leibler divergence for various probabilistic models. Rather than considering a convex combination of the initial estimators $f_1, \ldots, f_N$, our…

Statistics Theory · Mathematics 2016-01-22 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best…

Populations and Evolution · Quantitative Biology 2023-06-13 Lucy D'Agostino McGowan , Shirlee Wohl , Justin Lessler

Boolean tensor decomposition approximates data of multi-way binary relationships as product of interpretable low-rank binary factors, following the rules of Boolean algebra. Here, we present its first probabilistic treatment. We facilitate…

Machine Learning · Statistics 2018-05-15 Tammo Rukat , Chris C. Holmes , Christopher Yau

Many fundamental questions concerning the emergence and subsequent evolution of eukaryotic exon-intron organization are still unsettled. Genome-scale comparative studies, which can shed light on crucial aspects of eukaryotic evolution,…

Populations and Evolution · Quantitative Biology 2007-05-23 Miklós Csűrös , J. Andrew Holey , Igor B. Rogozin

We propose a statistical method to test whether two phylogenetic trees with given alignments are significantly incongruent. Our method compares the two distributions of phylogenetic trees given by the input alignments, instead of comparing…

Populations and Evolution · Quantitative Biology 2010-04-14 Elissaveta Arnaoudova , David Haws , Peter Huggins , Jerzy W. Jaromczyk , Neil Moore , Chris Schardl , Ruriko Yoshida

Modern population genetics studies typically involve genome-wide genotyping of individuals from a diverse network of ancestries. An important, unsolved problem is how to formulate and estimate probabilistic models of observed genotypes that…

Populations and Evolution · Quantitative Biology 2017-01-10 Wei Hao , Minsun Song , John D. Storey

This paper focuses on the estimation of partially observed branching processes. First, the estimators from a frequentist perspective proposed in the literature are reviewed. The main objective of this paper is to present computational tools…

Computation · Statistics 2026-05-21 Miguel González , Inés M. del Puerto , Manuel Serrano-Pastor

Biological data objects often have both of the following features: (i) they are functions rather than single numbers or vectors, and (ii) they are correlated due to phylogenetic relationships. In this paper we give a flexible statistical…

Quantitative Methods · Quantitative Biology 2012-12-20 Nick S. Jones , John Moriarty

As a technique to investigate link-level loss rates of a computer network with low operational cost, loss tomography has received considerable attentions in recent years. A number of parameter estimation methods have been proposed for loss…

Methodology · Statistics 2015-10-27 Ke Deng , Yang Li , Weiping Zhu , Jun S. Liu

Phylogenetically informed k-mers, or phylo-k-mers for short, are k-mers that are predicted to appear within a given genomic region at predefined locations of a fixed phylogeny. Given a reference alignment for this genomic region and…

Quantitative Methods · Quantitative Biology 2022-09-21 Nikolai Romashchenko , Benjamin Linard , Fabio Pardi , Eric Rivals

In this article, a Probability Mass Function (PMF) estimation method which tames the curse of dimensionality is proposed. This method, called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D, has for principle to partially…

Signal Processing · Electrical Eng. & Systems 2025-09-08 Philippe Flores , Konstantin Usevich , David Brie

Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history and numerous applications notwithstanding, inference of phylogenetic trees from sequence data remains…

Populations and Evolution · Quantitative Biology 2024-03-26 Mingyang Zhou , Zichao Yan , Elliot Layne , Nikolay Malkin , Dinghuai Zhang , Moksh Jain , Mathieu Blanchette , Yoshua Bengio

The evolution of molecular and phenotypic traits is commonly modelled using Markov processes along a phylogeny. This phylogeny can be a tree, or a network if it includes reticulations, representing events such as hybridization or admixture.…

Populations and Evolution · Quantitative Biology 2024-08-28 Benjamin Teo , Paul Bastide , Cécile Ané