Brian R. Moore

A Hierarchical Bayesian Mixture Model forInferring the Expression State of Genes inTranscriptomes

This paper introduces a hierarchical Bayesian mixture model to infer gene expression states from transcriptomic data, showing high accuracy in both simulated and empirical datasets.

TESS: Bayesian inference of lineage diversification rates from (incompletely sampled) molecular phylogenies in R

TESS estimates lineage diversification rates from molecular phylogenies using Bayesian methods, accommodating incomplete sampling and various diversification models.

A Bayesian Approach for Detecting Mass-Extinction Events When Rates of Lineage Diversification Vary

This paper introduces a Bayesian method to detect mass-extinction events from molecular phylogenies, showing it can accurately identify extinction events even with background diversification rate variation.

Bayesian Inference of Divergence Times and Feeding Evolution in Grey Mullets (Mugilidae)

This study estimates divergence times and explores feeding evolution in grey mullets using phylogenetic analysis and correlates feeding preferences with habitat, body size, and geographic distribution.

How Well Can We Detect Shifts in Rates of Lineage Diversification? A Simulation Study of Sequential AIC Methods

This paper evaluates the performance of MEDUSA, a method for detecting shifts in lineage diversification rates, through simulations revealing high Type I error and biased parameter estimates.