B. Rannala

PrioriTree helps researchers assess prior sensitivity in discrete-geographic phylodynamic models by generating BEAST input files and summarizing outputs for robust Bayesian inference.

This paper develops a Bayesian method to estimate the integration times of latent HIV sequences using serial viral sequences and applies it to patient data.

Phylodynamic analyses reveal that variation in rates of early geographic spread of COVID-19 are correlated with intervention measures.

This study evaluates how gene flow affects species tree estimation methods and finds the majority-vote method is more robust than UPGMA and likelihood methods under gene flow scenarios.

The paper implements a Bayesian model to infer introgression events using genomic data and applies it to study hybrid speciation in mosquito species.

The paper evaluates Bayesian species delimitation methods, showing BPP over-splits populations and struggles to distinguish speciation from population splits, and recommends using full likelihood analysis over PHRAPL.