Randomness is inherent to biochemistry: at each instant, the sequence of reactions that fires is a matter of chance. Some biological systems exploit such randomness, choosing between different outcomes stochastically ? in effect, hedging their bets with a portfolio of responses for different environmental conditions. In this paper, we discuss techniques for synthesizing such stochastic behavior in engineered biochemical systems. We propose a general method for designing a set of biochemical reactions that produces different combinations of molecular types according to a specified probability distribution. The response is precise and robust to perturbations. Furthermore, it is programmable: the probability distribution is a function of the quantities of input types. The method is modular and extensible. We discuss strategies for implementing various functional dependencies: linear, logarithmic, exponential, etc. This work has potential applications in domains such as biochemical sensin...
Brian Fett, Jehoshua Bruck, Marc D. Riedel