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Programmability of chemical reaction networks


Cook, M; Soloveichik, D; Winfree, E; Bruck, J (2009). Programmability of chemical reaction networks. In: Condon, A; Harel, D; Kok, J N; Salomaa, A; Winfree, E. Algorithmic bioprocesses. Pt. 8: Biochemical reactions. Berlin : Springer, 543-584.

Abstract

Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri Nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior.

Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri Nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior.

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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2009
Deposited On:01 Mar 2010 10:46
Last Modified:05 Apr 2016 13:59
Publisher:Springer
Series Name:Natural Computing Series
ISSN:1619-7127
ISBN:978-3-540-88868-0 (P) 978-3-540-88869-7 (E)
Publisher DOI:10.1007/978-3-540-88869-7_27
Related URLs:http://www.ini.uzh.ch/node/24319 (Organisation)
http://caltechparadise.library.caltech.edu/119/
Permanent URL: http://doi.org/10.5167/uzh-31951

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