Accuracy of the Michaelis-Menten approximation when analysing effects of molecular noise.

ABSTRACT: Quantitative biology relies on the construction of accurate mathematical models, yet the effectiveness of these models is often predicated on making simplifying approximations that allow for direct comparisons with available experimental data. The Michaelis-Menten (MM) approximation is widely used in both deterministic and discrete stochastic models of intracellular reaction networks, owing to the ubiquity of enzymatic activity in cellular processes and the clear biochemical interpretation of its parameters. However, it is not well understood how the approximation applies to the discrete stochastic case or how it extends to spatially inhomogeneous systems. We study the behaviour of the discrete stochastic MM approximation as a function of system size and show that significant errors can oc

SUBMITTER: Lawson MJ 

PROVIDER: S-EPMC4424680 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature