Andrew J. Black

The paper develops an agent-based model and neural likelihood estimator to infer parameters of yeast colony growth from time series data, improving parameter estimation and prediction accuracy compared to approximate Bayesian computation.

The paper models spiral colony morphology in yeast using an agent-based model and Bayesian inference to infer hyphal growth parameters.

The paper uses an off-lattice agent-based model and experimental data to show that budding mechanisms and nutrient concentration drive filamentous yeast colony morphology.