The large-scale engineering of novel bacterial systems is a complex, challenging task. Although small circuits can be designed manually, using the domain knowledge of the designer, this approach is not feasible for designs involving multiple pathways or even complete genomes. In this chapter, we address the value of computational intelligence approaches to the design of synthetic genetic circuits. Computational intelligence algorithms were designed to operate in complex, poorly understood domains in which the quality of a solution is more important than the route taken to achieve it and, as such, are potentially valuable to synthetic biology. To date, evolutionary computation has been used extensively in this field, but other computational intelligence algorithms, of potentially equal value, have been neglected. We review the basic principles of these algorithms and the way in which they have been, and may in the future be, of value in synthetic biology.
|Number of pages||37|
|Journal||Methods in Microbiology|
|Publication status||Published - 2013|