Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-17630
Soloveichik, D; Cook, M; Winfree, E; Bruck, J (2008). Computation with finite stochastic chemical reaction networks. Natural Computing, 7(4):615-633.
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A highly desired part of the synthetic biology toolbox is an embedded chemical microcontroller, capable of autonomously following a logic program specified by a set of instructions, and interacting with its cellular environment. Strategies for incorporating logic in aqueous chemistry have focused primarily on implementing components, such as logic gates, that are composed into larger circuits, with each logic gate in the circuit corresponding to one or more molecular species. With this paradigm, designing and producing new molecular species is necessary to perform larger computations. An alternative approach begins by noticing that chemical systems on the small scale are fundamentally discrete and stochastic. In particular, the exact molecular counts of each molecular species present, is an intrinsically available form of information. This might appear to be a very weak form of information, perhaps quite difficult for computations to utilize. Indeed, it has been shown that error-free Turing universal computation is impossible in this setting. Nevertheless, we show a design of a chemical computer that achieves fast and reliable Turing-universal computation using molecular counts. Our scheme uses only a small number of different molecular species to do computation of arbitrary complexity. The total probability of error of the computation can be made arbitrarily small (but not zero) by adjusting the initial molecular counts of certain species. While physical implementations would be difficult, these results demonstrate that molecular counts can be a useful form of information for small molecular systems such as those operating within cellular environments.
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|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Neuroinformatics|
|Dewey Decimal Classification:||570 Life sciences; biology|
|Uncontrolled Keywords:||Stochastic chemical kinetics - Molecular counts - Turing-universal computation - Probabilistic computation|
|Deposited On:||11 Mar 2009 08:02|
|Last Modified:||05 Apr 2016 13:10|
|Other Identification Number:||ini:12225|
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