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Statistical inference in evolutionary models with site-dependence is a long-standing challenge in phylogenetics and computational biology. We consider the problem of approximating marginal sequence likelihoods under dependent-site models of…

Computation · Statistics 2025-11-12 Joseph Mathews , Scott C. Schmidler

We investigate the infinitely many demes limit of the genealogy of a sample of individuals from a subdivided population subject to sporadic mass extinction events. By exploiting a separation of timescales property of Wright's island model,…

Probability · Mathematics 2009-01-29 Jesse E. Taylor , Amandine Veber

This paper introduces a framework for speeding up Bayesian inference conducted in presence of large datasets. We design a Markov chain whose transition kernel uses an (unknown) fraction of (fixed size) of the available data that is randomly…

Methodology · Statistics 2018-06-01 Florian Maire , Nial Friel , Pierre Alquier

Human populations have a complex history of introgression and of changing population size. Human genetic variation has been affected by both these processes, so that inference of past population size depends upon the pattern of gene flow…

Populations and Evolution · Quantitative Biology 2017-03-29 John Hawks

Pedigrees, or family trees, are graphs of family relationships that are used to study inheritance. A fundamental problem in computational biology is to find, for a pedigree with $n$ individuals genotyped at every site, a set of…

Data Structures and Algorithms · Computer Science 2016-02-16 Bonnie Kirkpatrick

Phylogenetic methods, traditionally used in biology to trace the evolutionary relationships among species, are emerging as a powerful framework to reconstruct evolutionary processes in galaxies from chemical information. We apply galactic…

Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle whole-genome mutation data due to their…

Methodology · Statistics 2023-01-02 Saptarshi Chakraborty , Zoe Guan , Colin B. Begg , Ronglai Shen

This article presents a comprehensive study of the continuous McKendrick model, which serves as a foundational framework in population dynamics and epidemiology. The model is formulated through partial differential equations that describe…

Populations and Evolution · Quantitative Biology 2026-01-23 Dragos-Patru Covei

Under the multispecies coalescent model of molecular evolution, gene trees have independent evolutionary histories within a shared species tree. In comparison, supermatrix concatenation methods assume that gene trees share a single common…

Populations and Evolution · Quantitative Biology 2016-06-13 Huw A. Ogilvie , Joseph Heled , Dong Xie , Alexei J. Drummond

Many commonly studied species now have more than one chromosome-scale genome assembly, revealing a large amount of genetic diversity previously missed by approaches that map short reads to a single reference. However, many species still…

Populations and Evolution · Quantitative Biology 2024-09-19 Miles D. Roberts , Olivia Davis , Emily B. Josephs , Robert J. Williamson

One of the main aims in phylogenetics is the estimation of ancestral sequences based on present-day data like, for instance, DNA alignments. One way to estimate the data of the last common ancestor of a given set of species is to first…

Populations and Evolution · Quantitative Biology 2017-02-07 Lina Herbst , Mareike Fischer

Statistical matching methods are widely used in the social and health sciences to estimate causal effects using observational data. Often the objective is to find comparable groups with similar covariate distributions in a dataset, with the…

Applications · Statistics 2021-01-19 Felix Bestehorn , Maike Bestehorn , Christian Kirches

Modern statistical inference tasks often require iterative optimization methods to compute the solution. Convergence analysis from an optimization viewpoint only informs us how well the solution is approximated numerically but overlooks the…

Machine Learning · Statistics 2020-07-27 Tengyuan Liang , Weijie Su

Recently, \textit{diffusion history inference} has become an emerging research topic due to its great benefits for various applications, whose purpose is to reconstruct the missing histories of information diffusion traces according to…

Social and Information Networks · Computer Science 2017-08-24 Yanchao Sun , Cong Qian , Ning Yang , Philip S. Yu

Full likelihood inference under Kingman's coalescent is a computationally challenging problem to which importance sampling (IS) and the product of approximate conditionals (PAC) method have been applied successfully. Both methods can be…

Probability · Mathematics 2016-08-29 Jere Koskela , Paul A. Jenkins , Dario Spano

Populations evolving under the joint influence of recombination and resampling (traditionally known as genetic drift) are investigated. First, we summarise and adapt a deterministic approach, as valid for infinite populations, which assumes…

Populations and Evolution · Quantitative Biology 2009-02-20 Ellen Baake , Inke Herms

Scientific practice typically involves repeatedly studying a system, each time trying to unravel a different perspective. In each study, the scientist may take measurements under different experimental conditions (interventions,…

Machine Learning · Statistics 2014-03-11 Sofia Triantafillou , Ioannis Tsamardinos

Parental origin effects play an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parental origin effects and is often convenient to collect in practice. Most existing…

Methodology · Statistics 2022-08-11 Yuang Tian , Hong Zhang , Alexandre Bureau , Hagit Hochner , Jinbo Chen

We present a novel approach for generating minority samples that live on low-density regions of a data manifold. Our framework is built upon diffusion models, leveraging the principle of guided sampling that incorporates an arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Soobin Um , Jong Chul Ye

We show that evolutionary computation can be implemented as standard Markov-chain Monte-Carlo (MCMC) sampling. With some care, `genetic algorithms' can be constructed that are reversible Markov chains that satisfy detailed balance; it…

Populations and Evolution · Quantitative Biology 2014-02-13 Chris Watkins , Yvonne Buttkewitz