Computational expressiveness of Genetic Systems

  • Authors:
  • Nadia Busi;Claudio Zandron

  • Affiliations:
  • Dipartimento di Scienze dellInformazione, Università di Bologna, Mura A. Zamboni 7, I-40127 Bologna, Italy;Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, Viale Sarca 336, I-20126 Milano, Italy

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2009

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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.