The ability to build genetic circuits with a reproducible response to external stimuli requires the development of both experimental techniques as well as rigorous theoretical design methodologies.
The genes and gene products involved in the response to a signal make up a genetic regulatory network. The development of robust, reliable and efficient novel gene regulatory circuits requires a mathematical description of this system. Until now, hundreds or even thousands of diverse GRN have been characterized experimentally, providing a wealth of data that can be used to infer empirical models of genetic circuits using model inference techniques akin to those employed in control engineering.
Changes in bacterial gene expression in response to a signal are often mediated by the products of regulator genes. Regulator genes encode signal-responsive proteins that act as activators or repressors of the expression level of effector genes. Therefore a gene regulatory network can be viewed as a complex assembly of interconnected regulatory units that can be analysed or manipulated using rigorous methodologies analogous to those in control engineering.
The aim of this project is to develop a novel framework for modelling, analysis and design of basic genetic circuits that is rooted in theoretical control theory. Such an approach promises to offer great insight into the underlying design principles of GRN, better understanding of cellular functions and in the engineering of novel gene regulatory circuits.