Alexei J. Drummond

This paper introduces KRegCCD, a new Bayesian phylogenetic model that improves posterior tree estimation and enables topology testing by providing full support over tree space.

This paper introduces a hierarchical clock-mixture model for Bayesian phylogenetic dating to better handle uncertainty in clock choice and improve timescale estimation.

The paper uses single-cell whole-genome sequencing and Bayesian phylodynamic modeling to show colorectal tumors often originate decades before diagnosis and expand rapidly in the last two years.

This paper introduces a Bayesian Model Averaging framework for phylodynamic inference that integrates multiple coalescent models to better capture demographic histories without pre-specifying a single model.

This paper introduces a Bayesian method for summarizing phylogenetic tree posteriors using clade probabilities, showing it performs as well or better than existing methods.

This paper describes good practices for validating Bayesian models in computational biology and introduces tools to automate validation protocols.

The paper introduces entropy-based rogue detection algorithms to improve Bayesian phylogenetic analysis by identifying and removing rogue taxa and clades that distort tree distributions.

The paper develops Bayesian methods to estimate phylogenies using continuous morphological characters and validates them through simulations and diverse datasets.

The paper analyzes SARS-CoV-2 genomic data from Colombia to study variant transmission dynamics and the impact of control measures during the first two years of the pandemic.

The paper reviews the evolutionary history of cotranscriptional editing in paramyxoviruses, showing multiple switches between P and V default modes and losses of the editing system.

The paper compares 12 stochastic transcription elongation models using Bayesian inference and force-velocity data from E. coli, S. cerevisiae, and T7 polymerases, showing differences in translocation rates and model applicability.

The paper compares 128 kinetic models of transcriptional pausing using approximate Bayesian computation to predict pause site locations in E. coli, finding structural parameters and translocation dynamics are key, while hypertranslocation and backtracking are not required.

SANTA-SIM simulates viral sequence evolution incorporating selection, recombination, and mutation to test inference methods.

The paper introduces TreeModelAdequacy, a tool to assess phylodynamic model adequacy using posterior predictive simulations, applied to Ebola and H1N1 influenza outbreak data.

StarBEAST2 improves species tree inference speed and accuracy by integrating population size analysis and relaxed clocks for substitution rate estimation.

bModelTest infers and marginalizes site models during Bayesian phylogenetic analysis, eliminating the need for pre-determined models.