Effective Computation of Stochastic Protein Kinetic Equation by Reducing Stiffness via Variable Transformation
For researchers simulating stochastic protein kinetics, this method reduces computational cost and errors, but the improvement is incremental.
The paper addresses stiffness in stochastic protein kinetic equations, which causes high computational cost and round-off errors. It proposes a variable transformation method to reduce stiffness, validated through theoretical and numerical analysis.
The stochastic protein kinetic equations can be stiff for certain parameters, which makes their numerical simulation rely on very small time step sizes, resulting in large computational cost and accumulated round-off errors. For such situation, we provide a method of reducing stiffness of the stochastic protein kinetic equation by means of a kind of variable transformation. Theoretical and numerical analysis show effectiveness of this method. Its generalization to a more general class of stochastic differential equation models is also discussed.