Fast Evaluation of Fluctuations in Biochemical Networks With the Linear Noise Approximation | Zendy

Johan Elf | Zendy; Måns Ehrenberg | Zendy

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Fast Evaluation of Fluctuations in Biochemical Networks With the Linear Noise Approximation

Author(s) -

Johan Elf,

Måns Ehrenberg

Publication year - 2003

Publication title -

genome research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 9.556

H-Index - 297

eISSN - 1549-5469

pISSN - 1088-9051

DOI - 10.1101/gr.1196503

Subject(s) - mesoscopic physics , master equation , statistical physics , noise (video) , biology , bifurcation , stochastic process , biological system , physics , mathematics , computer science , nonlinear system , quantum mechanics , statistics , artificial intelligence , image (mathematics) , quantum

Biochemical networks in single cells can display large fluctuations in molecule numbers, making mesoscopic approaches necessary for correct system descriptions. We present a general method that allows rapid characterization of the stochastic properties of intracellular networks. The starting point is a macroscopic description that identifies the system's elementary reactions in terms of rate laws and stoichiometries. From this formulation follows directly the stationary solution of the linear noise approximation (LNA) of the Master equation for all the components in the network. The method complements bifurcation studies of the system's parameter dependence by providing estimates of sizes, correlations, and time scales of stochastic fluctuations. We describe how the LNA can give precise system descriptions also near macroscopic instabilities by suitable variable changes and elimination of fast variables.

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