Stochastic P systems and the simulation of biochemical processes with dynamic compartments.
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.
Spicher
Antoine
A
IBISC-FRE 2873 CNRS & Université d'Evry, Genopole Tour Evry 2, 523 place des terrasses de l'Agora, 91000 Evry, France. aspicher@ibisc.fr
Michel
Olivier
O
Cieslak
Mikolaj
M
Giavitto
Jean-Louis
JL
Prusinkiewicz
Przemyslaw
P
D000465:Algorithms; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000502:physiology*; D008954:Models, Biological; D015233:Models, Statistical; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods
D020543:Proteome