Adelle Coster, University of New South Wales

The regulation of protein movements in cells is essential for life.  The hormone insulin regulates glucose uptake in mammalian fat and muscle cells – controlling the distribution of the glucose transporter protein GLUT4.

Mean field models have been able to identify some of the dominant processes that act in this cellular regulation system.  These deterministic models were optimised using data from multiple protocols and repeated experiments to simultaneously constrain the parameters and network structure. Stochastic models are required however, to test hypotheses about how the cell controls these processes at the molecular scale.  

Here we are interested in methods to quantitatively compare stochastic data with stochastic models – one candidate model is a closed queueing network.  We present a preliminary study using synthetic data to explore some measures of difference between the experimental datasets and the queueing model, with a view to informing parameter inference and model selection for this system.

Joint work with Maria Vlasiou and Marko Boon.