Abstract
Biochemical systems are often modeled with ordinary differential equations that are continuous and deterministic by nature. In recent years, with the development of new techniques to collect wet-lab data in a single cell, there are increasing concerns on the stochastic effect in cellular systems, where the small copy numbers of some reactant species in the cell may lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. In this chapter, we will review important algorithms for stochastic modeling and simulation of biochemical systems.
Keywords
- Stochastic Simulation
- Reaction Channel
- Biochemical System
- Uniform Random Number
- Stochastic Simulation Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Cao, Y. (2010). Stochastic Simulation for Biochemical Systems. In: Heath, L., Ramakrishnan, N. (eds) Problem Solving Handbook in Computational Biology and Bioinformatics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09760-2_10
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