Alexander P. Browning

The paper develops a model to show phenotypic adaptation drives drug resistance in BRAFV600E-mutant melanoma and suggests intermittent treatments may be more effective.

This paper introduces a Bayesian hierarchical framework to quantify both inter- and intra-experimental heterogeneity in dynamical processes using differential equations, demonstrating its robustness and flexibility.

This paper develops a stochastic model to assess the identifiability of phenotypic adaptation parameters from low-cell-count experiments and shows that cell-to-cell heterogeneity is non-identifiable from population-level data.

This study shows mechanical confinement drives phenotype switching in melanoma via chromatin remodeling mediated by HMGB2.

This paper analyzes identifiability in stochastic differential equation models using case studies and synthetic data, showing they can extract more parameter information than deterministic models.

The paper develops a theoretical framework for understanding bacterial persistence as a hedging strategy by integrating optimal control theory from finance and mathematical biology.

This paper applies optimal control theory to design combination therapies for acute myeloid leukaemia by analyzing control dynamics and pay-off functions.

This paper develops optimal chemotherapy strategies for AML by incorporating immune response into a stem cell model and applying optimal control theory.