Back to Search Start Over

Computation with finite stochastic chemical reaction networks

Authors :
Erik Winfree
Jehoshua Bruck
David Soloveichik
Matthew Cook
University of Zurich
Soloveichik, D
Source :
Natural Computing. 7:615-633
Publication Year :
2008
Publisher :
Springer Science and Business Media LLC, 2008.

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.

Details

ISSN :
15729796 and 15677818
Volume :
7
Database :
OpenAIRE
Journal :
Natural Computing
Accession number :
edsair.doi.dedup.....db7a8cc985c9e66bd875657187d5e684
Full Text :
https://doi.org/10.1007/s11047-008-9067-y