Stochastic P systems and the simulation of biochemical processes with dynamic compartments

Biosystems. 2008 Mar;91(3):458-72. doi: 10.1016/j.biosystems.2006.12.009. Epub 2007 Jul 17.

Abstract

We introduce a sequential rewriting strategy for P systems based on Gillespie's stochastic simulation algorithm, and show that the resulting formalism of stochastic P systems makes it possible to simulate biochemical processes in dynamically changing, nested compartments. Stochastic P systems have been implemented using the spatially explicit programming language MGS. Implementation examples include models of the Lotka-Volterra auto-catalytic system, and the life cycle of the Semliki Forest virus.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation / physiology*
  • Models, Biological*
  • Models, Statistical
  • Proteome / metabolism*
  • Signal Transduction / physiology*
  • Software*
  • Stochastic Processes
  • Systems Biology / methods

Substances

  • Proteome