|Institution:||University of Texas – Austin|
|Keywords:||Stochastic simulation; Molecular signaling; Enzyme reaction kinetics; Quasi-steady state approximation; Dimensionality reduction; Bistable molecular switch; Gillespie Algorithm|
|Full text PDF:||http://hdl.handle.net/2152/ETD-UT-2011-08-4067|
Biochemical reactions make up most of the activity in a cell. There is inherent stochasticity in the kinetic behavior of biochemical reactions which in turn governs the fate of various cellular processes. In this work, the precision of a method for dimensionality reduction for stochastic modeling of biochemical reactions is evaluated. Further, a method of stochastic simulation of reaction kinetics is implemented in case of a specific biochemical network involved in maintenance of long-term potentiation (LTP), the basic substrate for learning and memory formation. The dimensionality reduction method diverges significantly from a full stochastic model in prediction the variance of the fluctuations. The application of the stochastic simulation method to LTP modeling was used to find qualitative dependence of stochastic fluctuations on reaction volume and model parameters.