A theme in the last decade of computational systems biology has been how molecular noise is a factor that needs to be acc
ounted for, both to understand how gene regulatory networks are able to operate robustly in a noisy molecular environment and to explain phenotypic variability on both the individual cell and population levels. A particularly intriguing question is the interplay between spatial and temporal aspects of intracellular signaling is organized. Numerically, efficient spatial stochastic methods are needed to study this, but they become much more computationally demanding, largely due to the multiscale nature of the pathways and processes. A central area in the group is have the development of hybrid simulation methods for stochastic reaction-diffusion processes.
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- L. Meinecke, S. Engblom, A. Hellander, P. Lötstedt (2016) Analysis and design of jump coefficients in discrete stochastic diffusion models, SIAM J. Sci. Comput. 38(1), A55–A83.
- M. Lawson, L. Petzold and A. Hellander (2015) Accuracy of the Michaelis-Menten approximation when analyzing effects of molecular noise, Roy. Soc. Interface, 12(106) 2015
- S. Hellander, L. Petzold and A. Hellander (2015), Reaction rates for mesoscopic reaction-diffusion kinetics, Phys. Rev. E., 92(2), 023312.