On the Dynamics of an Artificial Regulatory Network

We investigate a simple artificial regulatory networks (ARNs) able to reproduce phenomena found in natural genetic regulatory networks. Notably heterochrony, a variation in timing of expression, is easily achievable by simple mutations of bits in the genome. It is argued that ARNs are useful and important new genetic representations for artificial evolution.

[1]  Paul J. Kennedy,et al.  A Model of Gene Expression and Regulation in an Artificial Cellular Organism , 2001, Complex Syst..

[2]  Kenneth J. McNamara,et al.  Heterochrony: The Evolution of Ontogeny , 1991 .

[3]  Gavin H. Thomas,et al.  Completing the E. coli proteome: a database of gene products characterised since the completion of the genome sequence , 1999, Bioinform..

[4]  Wolfgang Banzhaf,et al.  Genetic Programming: An Introduction , 1997 .

[5]  Torsten Reil,et al.  Dynamics of Gene Expression in an Artificial Genome - Implications for Biological and Artificial Ontogeny , 1999, ECAL.

[6]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[7]  W. Banzhaf.  Artificial Regulatory Networks and Genetic Programming , 2003 .

[8]  E. Davidson.  Genomic Regulatory Systems , 2001 .

[9]  M. Hirsch,et al.  Differential Equations, Dynamical Systems, and Linear Algebra , 1974 .

[10]  M. McKinney,et al.  Heterochrony: beyond words , 1999, Paleobiology.

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Ingo Rechenberg,et al.  Evolutionsstrategie '94 , 1994, Werkstatt Bionik und Evolutionstechnik.

[13]  L. Hood,et al.  The digital code of DNA , 2003, Nature.

[14]  Peter Nordin,et al.  Genetic programming - An Introduction: On the Automatic Evolution of Computer Programs and Its Applications , 1998 .

[15]  Peter Eggenberger,et al.  Evolving Morphologies of Simulated 3d Organisms Based on Differential Gene Expression , 1997 .

[16]  Rolf Pfeifer,et al.  Behavioural Selection Pressure Generates Hierarchical Genetic Regulatory Networks , 2002, GECCO.

[17]  James M. Bower,et al.  Computational modeling of genetic and biochemical networks , 2001 .

[18]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[19]  Hillol Kargupta.  Editorial: Computation in Gene Expression , 2004, Genetic Programming and Evolvable Machines.