Michael R. May

The paper develops a birth-death-reticulation model to analyze phylogenetic networks and applies it to study diversification in ferns, finding evidence that polyploids have lower diversification rates than diploids.

The paper introduces a Bayesian phylogenetic framework to infer divergence times, ancestral ranges, and diversification rates in Hawaiian plants without fossil calibration.

The paper develops Bayesian methods to quantify transcriptome turnover across species, finding accelerated gene expression changes in testes and accessory glands of Drosophila species.

This study models brain size-dependent diversification rates in birds, finding that larger brains reduce extinction rates, supporting the cognitive buffer hypothesis.

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.

The paper improves the maize reference genome using single molecule technologies, resulting in longer contigs and better annotation of repetitive elements and genes.

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

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.

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.

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.