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Robust statistical data modelling under potential model mis-specification often requires leaving the parametric world for the nonparametric. In the latter, parameters are infinite dimensional objects such as functions, probability…

Bayesian phylogenetics is vital for understanding evolutionary dynamics, and requires accurate and efficient approximation of posterior distributions over trees. In this work, we develop a variational Bayesian approach for ultrametric…

Machine Learning · Statistics 2026-02-16 Evan Sidrow , Alexandre Bouchard-Côté , Lloyd T. Elliott

There are few, if any, algorithms in statistical phylogenetics which are used more heavily than Felsenstein's 1973 pruning method for computing the likelihood of a tree. We present LvD, (Likelihood via Decomposition), an alternative to…

Populations and Evolution · Quantitative Biology 2026-01-28 David Bryant , Celine Scornavacca , David Swofford

Background: Fluorescent Timer proteins, which display time-dependent changes in their emission spectra, are invaluable for analyzing the temporal dynamics of cellular events at the single-cell level. We previously developed the…

Quantitative Methods · Quantitative Biology 2025-07-01 Masahiro Ono

Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune system. Densely sampled phylogenetic trees can contain special…

Populations and Evolution · Quantitative Biology 2020-06-03 Cheng Zhang , Vu Dinh , Frederick A. Matsen

Evolutionary relationships between species are usually inferred through phylogenetic analysis, which provides phylogenetic trees computed from allelic profiles built by sequencing specific regions of the sequences and abstracting them to…

Data Structures and Algorithms · Computer Science 2021-01-01 Luana Silva

Our paper deals with inferring simulator-based statistical models given some observed data. A simulator-based model is a parametrized mechanism which specifies how data are generated. It is thus also referred to as generative model. We…

Machine Learning · Statistics 2016-01-01 Michael U. Gutmann , Jukka Corander

varstan is an \proglang{R} package for Bayesian analysis of time series models using \proglang{Stan}. The package offers a dynamic way to choose a model, define priors in a wide range of distributions, check model's fit, and forecast with…

Computation · Statistics 2020-05-22 Izhar Asael Alonzo Matamoros , Cristian Andres Cruz Torres

Traditionally, phylogeny and sequence alignment are estimated separately: first estimate a multiple sequence alignment and then infer a phylogeny based on the sequence alignment estimated in the previous step. However, uncertainty in the…

Applications · Statistics 2014-11-25 Heejung Shim , Bret Larget

We propose the integral-equation formalism of population dynamics (IEPDYN) to describe the population dynamics of distinct configurational states. According to classical reaction dynamics theory, the probability density associated with a…

Chemical Physics · Physics 2026-03-25 Kento Kasahara , Ryo Okabe , Chia-en A. Chang , Toshifumi mori , Nobuyuki Matubayasi

The parameters of many classes of birth-death processes cannot be inferred uniquely from phylogenetic trees: infinitely many parameter combinations yield the same distribution of phylogenetic trees. Here, we show that parameter…

Populations and Evolution · Quantitative Biology 2026-04-21 Tobias Dieselhorst , Tanja Stadler

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of…

Methodology · Statistics 2017-08-01 Carter T. Butts , Christopher Steven Marcum

By providing a framework of accounting for the shared ancestry inherent to all life, phylogenetics is becoming the statistical foundation of biology. The importance of model choice continues to grow as phylogenetic models continue to…

Populations and Evolution · Quantitative Biology 2019-02-05 Jamie R. Oaks , Kerry A. Cobb , Vladimir N. Minin , Adam D. Leaché

The Persistent-Phylogeny Model is an extension of the widely studied Perfect-Phylogeny Model, encompassing a broader range of evolutionary phenomena. Biological and algorithmic questions concerning persistent phylogeny have been intensely…

Populations and Evolution · Quantitative Biology 2015-06-03 Dan Gusfield

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along…

Populations and Evolution · Quantitative Biology 2015-06-05 Alexandre Bouchard-Côté , Michael I. Jordan

phyloDB is a modular and extensible framework for large-scale phylogenetic analyses, which are essential for understanding epidemics evolution. It relies on the Neo4j graph database for data storage and processing, providing a schema and an…

Databases · Computer Science 2023-10-20 Bruno Lourenço , Cátia Vaz , Miguel E. Coimbra , Alexandre P. Francisco

Mendelian randomization is a powerful tool for causal inference in observational studies. The two-sample summary-data design, which estimates genetic associations with exposures and outcomes in separate cohorts, is the most widely used…

Methodology · Statistics 2026-04-29 Dingke Tang , Xuming He , Shu Yang

Inference of the marginal likelihood of sample allele configurations using backward algorithms yields identical results with the Kingman coalescent, the Moran model, and the diffusion model (up to a scaling of time). For inference of…

Populations and Evolution · Quantitative Biology 2021-12-20 Claus Vogl , Sandra Peer , Lynette Caitlin Mikula

Phylogenetic comparative methods correct for shared evolutionary history among a set of non-independent organisms by modeling sample traits as arising from a diffusion process along on the branches of a possibly unknown history. To…

Applications · Statistics 2020-09-30 Paul Bastide , Lam Si Tung Ho , Guy Baele , Philippe Lemey , Marc A Suchard

Powerful generative AI models of protein-ligand structure have recently been proposed, but few of these methods support both flexible protein-ligand docking and affinity estimation. Of those that do, none can directly model multiple binding…

Machine Learning · Computer Science 2025-03-25 Alex Morehead , Jianlin Cheng
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