Synthesizing Stochasticity in Biochemical Systems
- Creators
- Fett, Brian
- Bruck, Jehoshua
- Riedel, Marc D.
Abstract
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 sensing, drug production, and disease treatment. Moreover, it provides a framework for analyzing and characterizing the stochastic dynamics in natural biochemical systems such as the lysis/lysogeny switch of the lambda bacteriophage.
Additional Information
This work is supported in part by the "Alpha Project" at the Center for Genomic Experimentation and Computation, an NIH Center of Excellence (grant no. P50 HG02370). Also available from http://www.paradise.caltech.edu/papers/etr081.pdfFiles
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Additional details
- Eprint ID
- 26117
- Resolver ID
- CaltechPARADISE:2007.ETR081
- Created
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2008-02-19Created from EPrint's datestamp field
- Updated
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2019-11-22Created from EPrint's last_modified field
- Caltech groups
- Parallel and Distributed Systems Group