Eric Ron

This paper develops a sequential experiment design strategy to efficiently identify discrete stochastic models for gene expression using single-cell data.

The paper uses single-cell experiments and stochastic modeling to uncover mechanisms of GR dynamics and DUSP1 transcription regulation in response to glucocorticoids.

This paper proposes a hybrid computational pipeline combining mechanistic models and machine learning to design single-color multiplexed Nascent Chain Tracking experiments capable of resolving multiple mRNA species.