Stiffness detection and reduction in discrete stochastic simulation of biochemical systems

  • Pu Y
  • Watson L
  • Cao Y
  • 13


    Mendeley users who have this article in their library.
  • 5


    Citations of this article.


Typical multiscale biochemical models contain fast-scale and slow-scale reactions, where "fast" reactions fire much more frequently than "slow" ones. This feature often causes stiffness in discrete stochastic simulation methods such as Gillespie's algorithm and the Tau-Leaping method leading to inefficient simulation. This paper proposes a new strategy to automatically detect stiffness and identify species that cause stiffness for the Tau-Leaping method, as well as two stiffness reduction methods. Numerical results on a stiff decaying dimerization model and a heat shock protein regulation model demonstrate the efficiency and accuracy of the proposed methods for multiscale biochemical systems.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Yang Pu

  • Layne T. Watson

  • Yang Cao

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free