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Computation with finite stochastic chemical reaction networks

Soloveichik, David and Cook, Matthew and Winfree, Erik and Bruck, Jehoshua (2008) Computation with finite stochastic chemical reaction networks. Natural Computing, 7 (4). pp. 615-633. ISSN 1567-7818. https://resolver.caltech.edu/CaltechAUTHORS:20111020-132840264

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Abstract

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.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1007/s11047-008-9067-yDOIArticle
https://rdcu.be/4gI4PublisherFree ReadCube access
http://resolver.caltech.edu/CaltechPARADISE:2007.ETR085Related ItemTechnical Report
ORCID:
AuthorORCID
Winfree, Erik0000-0002-5899-7523
Additional Information:© 2008 Springer Science+Business Media B.V. Published online: 2 February 2008. We thank G. Zavattaro for pointing out an error in an earlier version of this manuscript. 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), as well as NSF Grant No. 0523761 and NIMH Training Grant MH19138-15.
Funders:
Funding AgencyGrant Number
NIHP50 HG02370
NSFCCF-0523761
NIH Predoctoral FellowshipMH19138-15
Subject Keywords:Stochastic chemical kinetics; Molecular counts; Turing-universal computation; Probabilistic computation
Issue or Number:4
Record Number:CaltechAUTHORS:20111020-132840264
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20111020-132840264
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:27331
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:24 Oct 2011 22:12
Last Modified:03 Oct 2019 03:22

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