Dynamics of gene expression in an artificial genome

Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulatory networks from an artificial genome, represented by a sequence of nucleotides, and analyse how variations in the connectivity and degree of inhibition of the extracted networks affects the resulting classes of behaviours. For low connectivity systems were found to be very stable. Only with higher connectivity was a significant occurence of chaos found. Most interestingly, the peak in occurrence of chaos occurs perched on the edge of a phase transition in the occurrence of null attractors. 1 Network Behaviour and Structure in Gene Networks From a complex systems point of view, the behaviour of genetic regulatory networks depends strongly on their network structure. System level properties such as robustness, stability and epistasis are thought to derive more from the interactions between components than from ...

• Type: Conference
• Year: 2003
• Where: CEC
• Authors: Kai Willadsen, Janet Wiles
• Keywords: Artificial Intelligence, CEC 2003, Complex Systems, Genetic Regulatory Networks, Random Boolean Networks