Understanding the forces that influence natural variation within and among populations has
been a major objective of evolutionary biologists for decades. Motivated by the growth in …

Glacial cycles have played a dominant role in shaping the genetic structure and distribution
of biota in northwestern North America. The two major ice age refugia of Beringia and the …

What are the models used in phylogenetic analysis and what exactly is involved in Bayesian
evolutionary analysis using Markov chain Monte Carlo (MCMC) methods? How can you …

Approximate Bayesian computation (ABC) constitutes a class of computational methods
rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function …

Phylogeographical analyses have become commonplace for a myriad of organisms with the
advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a …

Abstract Approximate Bayesian Computation (ABC) methods, also known as likelihood-free
techniques, have appeared in the past ten years as the most satisfactory approach to …

Approximate Bayesian computation (ABC) is a popular approach to address inference
problems where the likelihood function is intractable, or expensive to calculate. To improve …

Genealogies estimated from haplotypic genetic data play a prominent role in various
biological disciplines in general and in phylogenetics, population genetics and …

Despite the importance of polyploidy and the increasing availability of new genomic data,
there remain important gaps in our knowledge of polyploid population genetics. These gaps …

Phylogeographic methods aim to infer migration trends and the history of sampled lineages
from genetic data. Applications of phylogeography are broad, and in the context of …