Abstract
Genetic Systems are a formalism inspired by genetic regulatory networks, suitable for modeling the interactions between genes and proteins, acting as regulatory products. The evolution is driven by genetic gates: a new object (representing a protein) is produced when all activator objects are available in the system, and no inhibitor object is present. Activators are not consumed by the application of such a rule. Objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires.
It is known that such systems are Turing powerful, either when we consider interleaving semantics (a single action is executed in each computational step) as well as if we consider maximal parallel semantics (all the rules that can be applied at a computational step must be applied). In this paper we investigate the power of inhibiting rules.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Blossey, R., Cardelli, L., Phillips, A.: A Compositional Approach to the Stochastic Dynamics of Gene Networks. In: Priami, C., Cardelli, L., Emmott, S. (eds.) Transactions on Computational Systems Biology IV. LNCS (LNBI), vol. 3939, pp. 99–122. Springer, Heidelberg (2006)
Busi, N., Pinna, G.M.: A Causal Semantics for Contextual P/T nets. In: Proc. ICTCS 1995, pp. 311–325. World Scientific, Singapore (1995)
Busi, N.: On the computational power of the mate/Bud/Drip brane calculus: Interleaving vs. Maximal parallelism. In: Freund, R., Păun, G., Rozenberg, G., Salomaa, A. (eds.) WMC 2005. LNCS, vol. 3850, pp. 144–158. Springer, Heidelberg (2006)
Busi, N., Zandron, C.: Computing with genetic gates, proteins, and membranes. In: Hoogeboom, H.J., Păun, G., Rozenberg, G., Salomaa, A. (eds.) WMC 2006. LNCS, vol. 4361, pp. 250–265. Springer, Heidelberg (2006)
Busi, N., Zandron, C.: Computational expressiveness of Genetic Systems (submitted)
Busi, N., Zandron, C.: Computing with Genetic Gates. In: Cooper, S.B., Löwe, B., Sorbi, A. (eds.) CiE 2007. LNCS, vol. 4497, pp. 105–114. Springer, Heidelberg (2007)
Busi, N., Zandron, C.: On the Computational Power of Genetic Gates with Interleaving Semantics: The Power of Inhibition and Degradation. In: Csuhaj-Varjú, E., Ésik, Z. (eds.) FCT 2007. LNCS, vol. 4639, pp. 173–186. Springer, Heidelberg (2007)
Cardelli, L.: Brane Calculi. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 257–278. Springer, Heidelberg (2005)
De Jong, H.: Modeling and Simulation of Genetic Regulatory Systems: A Literature Review. Journal of Computatonal Biology 9, 67–103 (2002)
Finkel, A., Schnoebelen, P.: Well-Structured Transition Systems Everywhere! Theoretical Computer Science 256, 63–92 (2001)
Freund, R.: Asynchronous P Systems and P Systems Working in the Sequential Mode. In: Mauri, G., Păun, G., Jesús Pérez-Jímenez, M., Rozenberg, G., Salomaa, A. (eds.) WMC 2004. LNCS, vol. 3365, pp. 36–62. Springer, Heidelberg (2005)
Minsky, M.L.: Computation: Finite and Infinite Machines. Prentice-Hall, Englewood Cliffs (1967)
Montanari, U., Rossi, F.: Contextual Nets. Acta Inform. 32(6), 545–596 (1995)
Păun, G.: Membrane Computing. An Introduction. Springer, Heidelberg (2002)
Reisig, W.: Petri nets: An Introduction. EATCS Monographs in Computer Science. Springer, Heidelberg (1985)
Shepherdson, J.C., Sturgis, J.E.: Computability of Recursive Functions. Journal of the ACM 10, 217–255 (1963)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Busi, N., Zandron, C. (2009). Genetic Systems without Inhibition Rules. In: Archibald, M., Brattka, V., Goranko, V., Löwe, B. (eds) Infinity in Logic and Computation. ILC 2007. Lecture Notes in Computer Science(), vol 5489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03092-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-03092-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03091-8
Online ISBN: 978-3-642-03092-5
eBook Packages: Computer ScienceComputer Science (R0)