Mark Sinzger-D’Angelo

This study investigates how different DNA damage stimuli regulate p53 target gene promoter activity through stochastic gene expression, revealing stimulus-specific activation and deactivation rates.

The paper models chemical reaction networks in a random environment using Hawkes processes to approximate marginal descriptions of the system.

The paper quantifies the mean expression levels in linear CRNs under a random environment, showing how heterogeneity affects the stationary mean.

The paper compares five null models for combination drug therapy, finding the Hand model to be biochemically most plausible due to its generalization of dose equivalence and resolution of model ambiguities.