Symmetry-Based model reduction for approximate stochastic analysis

Authors:
Kirill Batmanov;Celine Kuttler;Francois Lemaire;Cédric Lhoussaine;Cristian Versari
Affiliations:
Lifl (CNRS UMR 8022), University of Lille 1, France;Lifl (CNRS UMR 8022), University of Lille 1, France;Lifl (CNRS UMR 8022), University of Lille 1, France;Lifl (CNRS UMR 8022), University of Lille 1, France;Lifl (CNRS UMR 8022), University of Lille 1, France,Inria, Lille, France
Venue:
CMSB'12 Proceedings of the 10th international conference on Computational Methods in Systems Biology
Year:
2012

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Abstract

For models of cell-to-cell communication, with many reactions and species per cell, the computational cost of stochastic simulation soon becomes intractable. Deterministic methods, while computationally more efficient, may fail to contribute reliable approximations for those models. In this paper, we suggest a reduction for models of cell-to-cell communication, based on symmetries of the underlying reaction network. To carry out a stochastic analysis that otherwise comes at an excessive computational cost, we apply a moment closure (MC) approach. We illustrate with a community effect, that allows synchronization of a group of cells in animal development. Comparing the results of stochastic simulation with deterministic and MC approximation, we show the benefits of our approach. The reduction presented here is potentially applicable to a broad range of highly regular systems.