N. F. Mueller

Impact and mitigation of sampling bias to determine viral spread: evaluating discrete phylogeography through CTMC modeling and structured coalescent model approximations

This study evaluates how sampling bias affects viral spread inference using phylogeographic models and proposes strategies to mitigate its impact through simulation and empirical datasets.

Joint inference of species histories and gene flow

The paper introduces a method to infer species trees while accounting for gene flow, showing improved accuracy in species history reconstruction for mosquitoes.

Adaptive parallel tempering for BEAST 2

This paper introduces an adaptive parallel tempering method for Bayesian phylogenetics in BEAST2 to improve MCMC efficiency by automatically tuning temperatures for better state space exploration.

Inferring time-dependent migration and coalescence patterns from genetic sequence and predictor data in structured populations

The paper introduces a method to infer time-dependent migration and coalescence patterns in structured populations using predictors and applies it to Ebola virus data.

The Structured Coalescent and its Approximations

The paper presents an exact solution to the structured coalescent and improves approximations for phylogeographic analysis without inferring ancestral migration histories.

MASCOT: Parameter and state inference under the marginal structured coalescent approximation

The paper introduces MASCOT, an algorithm that improves parameter and state inference under the structured coalescent approximation, enabling analysis of larger datasets with more states.