title: Evolutionary computation for the design of a stochastic switch for synthetic genetic circuits.
abstract: Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.
authors.affiliation: School of Computing Science, Newcastle University, Newcastle upon Tyne UK NE1 7RU. j.s.hallinan@ncl.ac.uk
authors.forename: Jennifer S
authors.initials: JS
authors.lastname: Hallinan
authors.forename: Goksel
authors.initials: G
authors.lastname: Misirli
authors.forename: Anil
authors.initials: A
authors.lastname: Wipat
mesh_terms: D001412:Bacillus subtilis / Q000235:genetics*; D001426:Bacterial Proteins / Q000235:genetics*; D032701:Biomimetics / Q000379:methods*; D003198:Computer Simulation; D039301:Computers, Molecular; D019143:Evolution, Molecular; D015964:Gene Expression Regulation, Bacterial / Q000235:genetics*; D007438:Introns / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D058615:Synthetic Biology / Q000379:methods
chemical_list: D001426:Bacterial Proteins