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Abstract: This dissertation presents several novel stochastic modeling approaches that capture important aspects of calcium (Ca) signaling. First, we present a Ca release site modeling approach based on a Langevin description of stochastic Ca release. This Langevin model facilitates our investigation of correlations between successive puff/spark amplitudes, durations and inter-spark intervals, and how such puff/spark statistics depend on the number of channels per release site and the kinetics of Ca-mediated inactivation of open channels. Second, we show that when the Ca channel model is minimal, Langevin equations in a whole cell model involving a large number of release sites may be replaced by a single Fokker-Planck equation. This yields an extremely compact and efficient local/global whole cell model that reproduces and helps interpret recent experiments investigating Ca homeostasis in permeabilized ventricular myocytes. Last but not least, we present a population density and moment-based approach to modeling L-type Ca channels. Our approaches account for the effect of heterogeneity of local Ca signals on whole cell Ca currents. Moreover, they facilitate the study of domain Ca-mediated inactivation of L-type Ca channels.

Bio: Xiao Wang was born in Beijing, China in 1987. She attended Fudan University where she received a Bachelor of Science in Mathematics in 2010. She began graduate studies of mathematical biology in The Department of Applied Science at The College of William & Mary in August 2010. She received her Master of Science in Applied Science in May 2012 and continued her studies of mathematical biology in pursuit of a Doctorate of Philosophy.

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