Hybrid simulation of cellular behavior

Authors:
Thomas R. Kiehl;Robert M. Mattheyses;Melvin K. Simmons
Affiliations:
Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady NY 12309, USA;Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady NY 12309, USA;Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady NY 12309, USA
Venue:
Bioinformatics
Year:
2004

Citing 0
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Abstract

Motivation: To be valuable to biological or biomedical research, in silico methods must be scaled to complex pathways and large numbers of interacting molecular species. The correct method for performing such simulations, discrete event simulation by Monte Carlo generation, is computationally costly for large complex systems. Approximation of molecular behavior by continuous models fails to capture stochastic behavior that is essential to many biological phenomena. Results: We present a novel approach to building hybrid simulations in which some processes are simulated discretely, while other processes are handled in a continuous simulation by differential equations. This approach preserves the stochastic behavior of cellular pathways, yet enables scaling to large populations of molecules. We present an algorithm for synchronizing data in a hybrid simulation and discuss the trade-offs in such simulation. We have implemented the hybrid simulation algorithm and have validated it by simulating the statistical behavior of the well-known lambda phage switch. Hybrid simulation provides a new method for exploring the sources and nature of stochastic behavior in cells. Supplementary information: The SBML file for the lambda phage tests will be made available at the OUP site.