Rowan D. Brackston

This paper introduces solvable stochastic models of gene expression that account for multiple states and factors affecting transcript abundance, enabling analytical and computational solutions for gene regulation.

This study derives analytical solutions for gene expression models to show that heavy-tailed RNA copy number distributions arise from extrinsic noise, not intrinsic stochasticity.

The paper analyzes dynamical systems models of stem-cell differentiation to explore transition states and their role in cell fate changes.