Modelling the evolution of transcriptional control networks using stochastic simulations and evolutionary computational methods

Organisms live in a constantly varying environment with limited resources. In order to thrive, organisms need to be able to respond to environmental changes, to make best use of the available resources, or to protect themselves from potentially harmful agents. One way to achieve this is to regulate how the DNA is transcribed and then subsequently translated. The complex patterns of genes regulating other genes form transcription networks which have evolved over millions of years to achieve the complexity we see in organisms today. Whilst it is possible to disassemble the complex network into smaller functional modules or motifs using various lab-based techniques, these techniques do not allow us to examine the evolution of the motifs and networks, because it is not possible to run laboratory experiments lasting millions of years. One potential solution to this problem is to use computational techniques and perform the evolution in silico.