Stochastic sensitivity analysis in chemical kinetics

Sensitivity, robustness, and identifiability in stochastic chemical kinetics models.

We present a novel and simple method to numerically calculate Fisher information matrices for stochastic chemical kinetics models. The linear noise approximation is used to derive model equations and a likelihood function that leads to an efficient computational algorithm. Our approach reduces the problem of calculating the Fisher information matrix to solving a set of ordinary differential equ...

Stochastic Chemical Kinetics

where k is the rate constant. The stochastic approach to chemical kinetics is concerned with modeling chemical reactions in situations where the assumptions underlying equations of this type break down. In order to illustrate this, suppose that the reaction above is occuring in a drop of water of volume V , which contains only a very small number, say 3, of molecules of I. The kinetic equation ...

Efficiency of the Girsanov Transformation Approach for Parametric Sensitivity Analysis of Stochastic Chemical Kinetics

Abstract. For stochastic reaction networks consisting of several species, Monte Carlo methods are the most suitable for parametric sensitivity analysis. Most of the Monte Carlo methods for sensitivity analysis can be classified into three categories, the pathwise derivative (PD) method, the finite difference (FD) method and the Girsanov transformation (GT) method. It has been numerically observ...

Stochastic simulation of chemical kinetics.

Stochastic chemical kinetics describes the time evolution of a well-stirred chemically reacting system in a way that takes into account the fact that molecules come in whole numbers and exhibit some degree of randomness in their dynamical behavior. Researchers are increasingly using this approach to chemical kinetics in the analysis of cellular systems in biology, where the small molecular popu...

Numerical Solution Methods in Stochastic Chemical Kinetics