Modelling Molecular Processes by Individual-Based Simulations Applied to Actin Polymerisation - Simulation and Modeling Methodologies, Technologies and Application - page 182

any distribution, as well as spatial behaviour of molecules can be easily modelled.
Our model simulates actin polymerisation, an important key player for different cell
functions.
The spatial outcome of our model is comparable to alternative models of
Cardelli et al. (2009), using the stochastic π -calculus. Because the FLAME-framework
produces XML-files for each time step, we are also able to create an animated version
for tracking the filament formation (not shown here). Additionally a time dependent
analysis of the behaviour of the single molecules and the filaments can be done. The
limit in using the agent-based approach is only given by computational purposes.
Our overall aim is the development of a biophysical realistic model for actin poly-
merisation in human cells. The advantage of our approach is the possibility to to ex-
tend the simulation to a massive number of molecules with the aid of the parallelised
FLAME software version and, more important, the easy implementation of external in-
fluences. This should enable us to analyse observed phenomena of actin clustering on
titan pillar surface structures [14] with applications to implant technologies. This inter-
esting issue makes it necessary to include more proteins like capping proteins which
stop the elongation of the filament [23].
Acknowledgements. We are grateful for financial support of the research training
school “Welisa”, which is founded by the German Research Foundation (DFG 1505/1).
Furthermore the authors are thankful for the helpful advice of Prof. Mike Holcombe
and Mark Burkitt from the University of Sheffield.
References
1. Andrews, S.S., Bray, D.: Stochastic simulation of chemical reactions with spatial resolution
and single molecule detail. Phys. Biol. 1(3-4), 137-151 (2004)
2. Cardelli, L., Caron, E., Gardner, P., Kahramanogullari, O., Phillips, A.: A process model
of actin polymerisation. Electronic Notes in Theoretical Computer Science 229(1), 127-
144 (2009); Proceedings of the Second Workshop From Biology to Concurrency and Back
(FBTC 2008)
3. Cooper, J.A.: The role of actin polymerization in cell motility. Annu. Rev. Physiol. 53, 585-
605 (1991)
4. Corradini, F., Merelli, E., Vita, M.: A Multi-agent System for Modelling Carbohydrate Ox-
idation in Cell. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Lagana, A., Lee, H.P., Mun,
Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3481, pp. 1264-1273. Springer,
Heidelberg (2005)
5. Edelstein-Keshet, L., Ermentrout, G.B.: Models for the length distributions of actin fila-
ments: I. simple polymerization and fragmentation. Bull. Math. Biol. 60(3), 449-475 (1998)
6. Emonet, T., Macal, C.M., North, M.J., Wickersham, C.E., Cluzel, P.: Agentcell: a digital
single-cell assay for bacterial chemotaxis. Bioinformatics 21(11), 2714-2721 (2005)
7. Fujiwara, I., Vavylonis, D., Pollard, T.D.: Polymerization kinetics of adp- and adp-pi-actin
determined by fluorescence microscopy. Proc. Natl. Acad. Sci. U. S. A. 104(21), 8827-8832
(2007)
8. Galletta, B.J., Mooren, O.L., Cooper, J.A.: Actin dynamics and endocytosis in yeast and
mammals. Curr. Opin. Biotechnol. Curr. Opin. Biotechnol. (July 2010) (in press)
9. Gheorghe, M., Stamatopoulou, I., Holcombe, M., Kefalas, P.: Modelling Dynamically Or-
ganised Colonies of Bio-entities. In: Banatre, J.-P., Fradet, P., Giavitto, J.-L., Michel, O.
(eds.) UPP 2004. LNCS, vol. 3566, pp. 207-224. Springer, Heidelberg (2005)