M. S. Hibbins

This paper develops new phylogenomic methods to account for gene tree discordance in evolutionary trait analysis, showing improved accuracy in estimating trait evolution rates.

This study uses supervised machine learning to distinguish between speciation and introgression histories using genomic data, showing high accuracy in simulated datasets.

This study uses gene expression data from wild tomatoes to show introgression affects quantitative trait evolution by generating convergent patterns across thousands of traits.

The paper develops a method to estimate hemiplasy probabilities in the presence of ILS and introgression, showing introgression increases hemiplasy likelihood and presents a tool for statistical inference.

The paper introduces a new test for introgression, D3, which uses single sequences from three taxa and shows comparable statistical power to existing methods.

The paper develops statistical methods to test hypotheses about introgression timing and direction using the multispecies network coalescent framework and applies them to yeast genomic data.

This study presents three new genome assemblies of Musa acuminata subspecies to investigate their rapid radiation and evolutionary relationships with M. balbisiana.