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Modeling and simulation of biochemical systems are important tasks because they can provide insights into complicated systems where traditional experimentation is expensive or impossible. Stochastic hybrid systems are an ideal modeling paradigm for biochemical systems because they combine continuous and discrete dynamics in a stochastic framework. Simulation of these systems is difficult because of the inherent error which is introduced near the boundaries. In this work we develop a method fordoi:10.1109/wsc.2008.4736143 dblp:conf/wsc/RileyR08 fatcat:v7osioxdurbydncl6mbkpsayy4