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Sparse grids and hybrid methods for the chemical master equation

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Abstract

The direct numerical solution of the chemical master equation (CME) is usually impossible due to the high dimension of the computational domain. The standard method for solution of the equation is to generate realizations of the chemical system by the stochastic simulation algorithm (SSA) by Gillespie and then taking averages over the trajectories. Two alternatives are described here using sparse grids and a hybrid method. Sparse grids, implemented as a combination of aggregated grids are used to address the curse of dimensionality of the CME. The aggregated components are selected using an adaptive procedure. In the hybrid method, some of the chemical species are represented macroscopically while the remaining species are simulated with SSA. The convergence of variants of the method is investigated for a growing number of trajectories. Two signaling cascades in molecular biology are simulated with the methods and compared to SSA results.

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Authors and Affiliations

  1. Centre for Mathematics and its Applications, MSI, Australian National University, Canberra, ACT, 0200, Australia

    Markus Hegland

  2. Division of Scientific Computing, Department of Information Technoloy, Uppsala University, 75105, Uppsala, Sweden

    Andreas Hellander & Per Lötstedt

Authors
  1. Markus Hegland
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  2. Andreas Hellander
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  3. Per Lötstedt
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Correspondence to Per Lötstedt.

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AMS subject classification (2000)

65C20, 60J25, 92C45

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Hegland, M., Hellander, A. & Lötstedt, P. Sparse grids and hybrid methods for the chemical master equation . Bit Numer Math 48, 265–283 (2008). https://doi.org/10.1007/s10543-008-0174-z

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  • DOI: https://doi.org/10.1007/s10543-008-0174-z

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