2014 Summer Undergraduate REU Program
University of Notre Dame
Bayesian Statistical Calibration of Stochastic Models for Infectious Disease Transmission - James Dillon Delaney
Stochastic simulations of diseases that are transmitted through human-to-human contact, like influenza, or through vectors, like malaria, have been used to assist public health professionals in understanding the spread and severity of epidemics and have been used to assist in the selection of intervention strategies, e.g. introduction of bed nets. Simulations may be based on stochastic S-I-R compartmental models or agent based models. In either case, Bayesian statistical methods may be used to estimate the model parameters using physical data, and to quantify uncertainty. The REU student will engage in independent computer experimentation to understand the properties of different modeling strategies as well as the Bayesian statistical computational tools that would be needed to estimate model parameters.
Modeling Length Regulation of Stereocilia - Alexandra Jilkine
Stereocilia are mechanosensitive actin-based protrusions of hair cells in the inner ear, whose length is very precisely regulated via an actin molecular treadmill mechanism. Recently, molecular motor transport has been shown to also play a role in this length regulation. The student will use available quantitative data to formulate a mathematical model of actin flux in stereocilia. The goal is to examine which aspect of actin dynamics (regulation of actin assembly at the tip, filament disassembly at the proximal end, or transport of monomers) might regulate the length of stereocilia. Existing mathematical models only consider the length regulation of a single stereocilium. However, stereocilia need to form a staircaselike bundle with multiple steady state lengths. We will consider models that allow the possibility of multiple steady state solutions.