Artificial gene regulatory networks are computational models that draw inspiration from biological networks of gene regulation. Since their inception they have been used to infer knowledge about gene regulation and as methods of computation. These computational models have been shown to possess properties typically found in the biological world, such as robustness and self organisation. Recently, it has become apparent that epigenetic mechanisms play an important role in gene regulation. This paper describes a new model,the Artificial Epigenetic Regulatory Network (AERN) which builds upon existing models by adding an epigenetic control layer. Our results demonstrate that AERNs are more adept at controlling multiple opposing trajectories when applied to a chaos control task within a conservative dynamical system, suggesting that AERNs are an interesting area for further investigation.
@article(SS-BIO-13-t, author = "Alexander P. Turner and Michael A. Lones and Luis A. Fuente and Susan Stepney and Leo S. D. Caves and Andy M. Tyrrell", title = "The incorporation of epigenetics in artificial gene regulatory networks", journal = "BioSystems", volume = 112, number = 2, pages = "56-62", year = 2013 )