Ammon Thompson

The paper introduces phyddle, a software tool using deep learning for phylogenetic modeling, and shows it accurately performs inference tasks even for models without tractable likelihoods.

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