Abstract
Random boolean networks (shortly, RBN) have proven useful in describing complex phenomena occurring at the unicellular level. It is therefore interesting to investigate how their dynamical behavior is affected by cell-cell interactions, which mimics those occurring in tissues in multicellular organisms. It has also been suggested that evolution may tend to adjust the parameters of the genetic network so that it operates close to a critical state, which should provide evolutionary advantage ; this hypothesis has received intriguing, although not definitive support from recent findings. It is therefore particularly interesting to consider how the tissue-like organization alters the dynamical behavior of the networks close to a critical state. In this paper we define a model tissue, which is a cellular automaton each of whose cells hosts a full RBN, and we report preliminary studies of the way in which the dynamics is affected.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kauffman, S.A.: Gene Regulation Networks: A Theory of their Global Structure and Behavior. Curr. Top. Dev. Biol. 6, 145–182 (1971)
Kauffman, S.A.: The origins of order. Oxford University Press, Oxford (1993)
Aldana, M., Coppersmith, S., Kadanoff, L.P.: Boolean Dynamics with Random Couplings. In: Kaplan, E., Marsden, J.E., Sreenivasan, K.R. (eds.) Perspectives and Problems in Nonlinear Science. Applied Mathematical Sciences Series, Springer, Heidelberg (2003), http://www.arXiv:cond-mat/0209571
Serra, R., Villani, M., Semeria, A.: Robustness to damage of biological and synthetic networks. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds.) ECAL 2003. LNCS (LNAI), vol. 2801, pp. 706–715. Springer, Heidelberg (2003)
Serra, R., Villani, M., Semeria, A.: Genetic network models and statistical properties of gene expression data in knock-out experiments. J. Theor. Biol. 227(1), 149–157 (2004)
Ramo, P., Kesseli, J., Yli-Harja, O.: Perturbation avalanches and criticality in gene regulatory networks Journal of Theoretical Biology (submitted, 2005)
Shmulevich, I., Kauffman, S.A.: Activities and Sensitivities in Boolean Network Models. Phys Rev. Lett. 93(4), 048701 (1-4) (2004)
Kauffman, S., Peterson, C., Samuelsson, B., Troein, C.: Genetic networks with canalyzing Boolean rules are always stable. PNAS 101(49) (2004)
Harvey, I., Bossomaier, T.: Time out of joint: Attractors in asynchronous random boolean networks. In: Husbands, P., Harvey, I. (eds.) Proceedings of the Fourth European Conference on Artificial Life (ECAL 1997), pp. 67–75. MIT Press, Cambridge (1997)
Kauffman, S.A.: Investigations. Oxford University Press, Oxford (2000)
Harris, S.E., Sawhill, B.K., Wuensche, A., Kauffman, S.A.: A model of transcriptional regulatory networks based on biases in the observed regulation rules. Complexity 7, 23–40 (2002)
Bastolla, U., Parisi, G.: The modular structure of Kauffman networks. Physica D 115, 219–233 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Villani, M., Serra, R., Ingrami, P., Kauffman, S.A. (2006). Coupled Random Boolean Network Forming an Artificial Tissue. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds) Cellular Automata. ACRI 2006. Lecture Notes in Computer Science, vol 4173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861201_63
Download citation
DOI: https://doi.org/10.1007/11861201_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40929-8
Online ISBN: 978-3-540-40932-8
eBook Packages: Computer ScienceComputer Science (R0)