While BioBricks offers many advantages, the challenge remains to build a device composed of synthetic gene networks that functions as predicted by design [12]. A good device ought therefore to provide predictability and reliability. Computational modeling can help evaluate the reliability and performance of the system before constructing the device [4]. Depending on computa- tional analysis, suboptimal BioBricks can be redesigned, replaced and optimized before physical construction and
Fig. 2.
162 Journal of Advanced
and Intelligent Informatics
Computational Intelligence Vol.17 No.2, 2013
assembly. Computational modeling is therefore essential to both design time and cost reduction.
Additionally, computers can aid in the automation of construction and the characterization of genetic parts. For instance, users can interrogate various behaviors of a device, such as its robustness and stability, on a high throughput basis [11, 12]. They may occasionally iden- tify unexpected behavior of the device through model- ing and simulation that speed up the system construc- tion process [4]. Such steps help address crucial issues such as optimal input concentration, reaction duration or requirement for steady or dynamic measurements [4]. Well-founded estimates from models allow the building of more predictable and reliable genetic devices to facilitate the planning of specific validation experiments.