John Reinitz

The paper develops a framework to analyze thermodynamic models of transcriptional regulation using experimental data from Drosophila embryos.

The paper presents a fully interpretable deep learning model for understanding DNA regulatory codes in gene expression, validated on Drosophila embryo data.

The paper analyzes gene regulation robustness in Drosophila using a sequence-level model, finding that enhancer length correlates with robustness to genetic perturbation.

The paper develops a two-state stochastic model for gene transcription in Drosophila embryos and shows it can produce bursts of varying sizes and durations, matching experimental data on eve gene stripe two formation.