We introduce Genetic Systems, a formalism inspired by genetic regulatory networks and suitable for modeling the interactions between the genes and the proteins, acting as regulatory products. The generation of new objects, representing proteins, is driven by genetic gates: a new object is produced when all the activator objects are available in the system, and no inhibitor object is available. Activators are not consumed by the application of such an evolution rule. Objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires. We investigate the computational expressiveness of Genetic Systems: we show that they are Turing equivalent by providing encodings of Random Access Machines in Genetic Systems. © 2008 Elsevier B.V. All rights reserved.
Zandron, C., Busi, N. (2009). Computational expressiveness of Genetic Systems. THEORETICAL COMPUTER SCIENCE, 410(4-5), 286-293 [10.1016/j.tcs.2008.09.041].
Computational expressiveness of Genetic Systems
ZANDRON, CLAUDIO;
2009
Abstract
We introduce Genetic Systems, a formalism inspired by genetic regulatory networks and suitable for modeling the interactions between the genes and the proteins, acting as regulatory products. The generation of new objects, representing proteins, is driven by genetic gates: a new object is produced when all the activator objects are available in the system, and no inhibitor object is available. Activators are not consumed by the application of such an evolution rule. Objects disappear because of degradation: each object is equipped with a lifetime, and the object decays when such a lifetime expires. We investigate the computational expressiveness of Genetic Systems: we show that they are Turing equivalent by providing encodings of Random Access Machines in Genetic Systems. © 2008 Elsevier B.V. All rights reserved.
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