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In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies…

Populations and Evolution · Quantitative Biology 2023-10-19 Alexander L. Lewanski , Michael C. Grundler , Gideon S. Bradburd

There is little debate about the importance of the ancestral recombination graph in population genetics. An important theoretical tool, the main obstacle to its widespread usage is the computational cost required to match the…

Populations and Evolution · Quantitative Biology 2026-05-14 Patrick Fournier , Fabrice Larribe

Ancestral recombination graphs (ARGs) encode the complete genealogical history of a population of recombining lineages. ARGs, and their succinct representation, tree sequences, are increasingly central to modern population genetics methods,…

Populations and Evolution · Quantitative Biology 2025-10-09 Christopher Talbot , Gideon Bradburd

Recombination is a powerful evolutionary process that shapes the genetic diversity observed in the populations of many species. Reconstructing genealogies in the presence of recombination from sequencing data is a very challenging problem,…

Populations and Evolution · Quantitative Biology 2022-06-01 Elizabeth Hayman , Anastasia Ignatieva , Jotun Hein

The ancestral recombination graph (ARG) is the model of choice in statistical genetics to model population ancestries. Software capable of simulating ARGs on a genome scale within a reasonable amount of time are now widely available for…

Genomics · Quantitative Biology 2026-04-15 Patrick Fournier , Fabrice Larribe

Summary: Ancestral recombination graphs (ARGs) are a complete representation of the genetic relationships between recombining lineages and are of central importance in population genetics. Recent breakthroughs in simulation and inference…

Populations and Evolution · Quantitative Biology 2025-08-07 James Kitchens , Yan Wong

Over the years, many approaches have been proposed to build ancestral recombination graphs (ARGs), graphs used to represent the genetic relationship between individuals. Among these methods, many rely on the assumption that the most likely…

Machine Learning · Computer Science 2025-06-16 Mélanie Raymond , Marie-Hélène Descary , Cédric Beaulac , Fabrice Larribe

The reconstruction of possible histories given a sample of genetic data in the presence of recombination and recurrent mutation is a challenging problem, but can provide key insights into the evolution of a population. We present KwARG,…

Populations and Evolution · Quantitative Biology 2021-05-14 Anastasia Ignatieva , Rune B. Lyngsø , Paul A. Jenkins , Jotun Hein

Pedigrees are directed acyclic graphs that represent ancestral relationships between individuals in a population. Based on a schematic recombination process, we describe two simple Markov models for sequences evolving on pedigrees - Model R…

Populations and Evolution · Quantitative Biology 2013-01-18 Bhalchandra D. Thatte

We present a new Markov chain Monte Carlo algorithm, implemented in software Arbores, for inferring the history of a sample of DNA sequences. Our principal innovation is a bridging procedure, previously applied only for simple stochastic…

Computation · Statistics 2019-03-06 Kari Heine , Alex Beskos , Ajay Jasra , David Balding , Maria De Iorio

The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene…

Quantitative Methods · Quantitative Biology 2016-09-28 Pablo G. Camara , Arnold J. Levine , Raul Rabadan

Retrieval-augmented generation (RAG) is a powerful technique that enhances downstream task execution by retrieving additional information, such as knowledge, skills, and tools from external sources. Graph, by its intrinsic "nodes connected…

We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double…

Genomics · Quantitative Biology 2014-05-13 Benedict Paten , Daniel R. Zerbino , Glenn Hickey , David Haussler

A quest to determine the complete sequence of a human DNA from telomere to telomere started three decades ago and was finally completed in 2021. This accomplishment was a result of a tremendous effort of numerous experts who engineered…

Genomics · Quantitative Biology 2022-06-03 Lovro Vrček , Xavier Bresson , Thomas Laurent , Martin Schmitz , Mile Šikić

Directed acyclic graphs are the basic representation of the structure underlying Bayesian networks, which represent multivariate probability distributions. In many practical applications, such as the reverse engineering of gene regulatory…

Computation · Statistics 2013-11-15 Jack Kuipers , Giusi Moffa

Designing flexible probabilistic models over tree topologies is important for developing efficient phylogenetic inference methods. To do that, previous works often leverage the similarity of tree topologies via hand-engineered heuristic…

Populations and Evolution · Quantitative Biology 2023-10-17 Tianyu Xie , Cheng Zhang

We analyse sequential Markov coalescent algorithms for populations with demographic structure: for a bottleneck model, a population-divergence model, and for a two-island model with migration. The sequential Markov coalescent method is an…

Populations and Evolution · Quantitative Biology 2025-10-01 A. Eriksson , B. Mahjani , B. Mehlig

D. Wilson~\cite{[Wi]} in the 1990's described a simple and efficient algorithm based on loop-erased random walks to sample uniform spanning trees and more generally weighted trees or forests spanning a given graph. This algorithm provides a…

Probability · Mathematics 2018-08-29 L. Avena , F. Castell , A. Gaudilliere , C. Melot

Retrieval-Augmented Generation (RAG) systems for biomedical literature are typically evaluated using ranking metrics like Mean Reciprocal Rank (MRR), which measure how well the system identifies the single most relevant chunk. We argue that…

Artificial Intelligence · Computer Science 2026-03-25 Pouria Mortezaagha , Arya Rahgozar
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