E-Cell 3.2.0p1 Released
eGFRD Simulator Prototype
A novel particle dynamics simulation code is under development towards eventual inclusion to the forthcoming E-Cell System version 4 platform.
eGFRD Simulator Prototype Now Available
An implementation of the enhanced Green's Function Reaction Dynamics (eGFRD) algorithm is now available for download here.
Version 0.3 of the code was first publicly released under GNU General Public License version 2 on Dec 22nd, 2008. Earlier versions 0.0, 0.1 and 0.2 of the code were released internally for testing purpose in 2007 and 2008.
The simulator code is under active development, and new versions will follow.
About the eGFRD algorithm
The principle idea of Green's Function Reaction Dynamics (GFRD) is to decompose the many-body reaction-diffusion problem into one- and two-body problems that can be solved analytically using Green's functions. In the original version of the algorithm [1] [2], a maximum time step was used such that each particle could interact with at most one other particle. Moreover, in GFRD the particles were updated simultaneously at each step. Although already up to five orders more efficient than conventional reaction Brownian Dynamics [1] [3] and also very accurate by its own right, the original GFRD algorithm is not exact, and suboptimal in terms of speed because of the synchronous nature of the update of the particles. Motivated by the work of Kalos, Levesque and Verlet [4] and that of Opplestrup, Bulatov, Gilmer, Kalos and Sadigh [5], in the enhanced version of GFRD, presented here, protective domains are put around single particles and pairs of particles, making the new scheme, called eGFRD, exact. Moreover, following Opplestrup et al. [5] and Gibson and Bruck [6], in eGFRD the particles are updated asynchronously. eGFRD is thus an exact, asynchronous, event-driven algorithm.
About the Code
The purpose of this prototype code written in mixed Python and C++ is to establish a solid and practical implementation of the algorithm, and to extend it into a form that is suitable for large-scale biochemical and cell simulations.
Part of the prototype is meant to be integrated into E-Cell System Version 4 software platform, of which one of the leading features will be multi-spatial representation, meaning that multiple sub-models with different classes and scales of representations of space can coexist and interplay in a simulation model.
| [1] | (1, 2) Simulating biochemical networks at the particle level and in time and space: Green's function reaction dynamics; J.S. Van Zon and P.R. ten Wolde Phys Rev Lett. 94 (2005) |
| [2] | Green's-function reaction dynamics: a particle-based approach for simulating biochemical networks in time and space; J. S. van Zon and P. R. ten Wolde Journal of Chemical Physics 123 (2005) |
| [3] | Reaction Brownian dynamics and the effect of spatial fluctuations on the gain of a push-pull network; M.J. Morelli, P.R. ten Wolde, J. Chem. Phys. 129 (2008) |
| [4] | Helium at zero temperature with hard-sphere and other forces; M.H. Kalos, D. Levesque and L. Verlet, Phys. Rev. A 9 (1974) |
| [5] | (1, 2) First-Passage Monte Carlo Algorithm: Diffusion without All the Hops; T. Opplestrup, V.V. Bulatov, G.H. Gilmer, M.H. Kalos, and B. Sadigh, Phys. Rev. Lett. 97 (2006) |
| [6] | Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels; M.A. Gibson and J. Bruck, J. Phys. Chem. A (2000) |
