Journal article

Programming discrete distributions with chemical reaction networks

Abstract:: We explore the range of probabilistic behaviours that can be engineered with Chemical Reaction Networks (CRNs). We give methods to “program” CRNs so that their steady state is chosen from some desired target distribution that has finite support in N^m, with m ≥ 1. Moreover, any distribution with countable infinite support can be approximated with arbitrarily small error under the L¹ norm. We also give optimized schemes for special distributions, including the uniform distribution. Finally, we formulate a calculus to compute on distributions that is complete for finite support distributions, and can be compiled to a restricted class of CRNs that at steady state realize those distributions.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Cardelli, L., Kwiatkowska, M., & Laurenti, L. (2017). Programming discrete distributions with chemical reaction networks. Natural Computing, 17(1), 131–145.

MLA Style

Cardelli, L, et al. “Programming Discrete Distributions with Chemical Reaction Networks.” Natural Computing, vol. 17, no. 1, 2017, pp. 131–45.

Chicago Style

Cardelli, L, M Kwiatkowska, and L Laurenti. 2017. “Programming Discrete Distributions with Chemical Reaction Networks.” Natural Computing 17 (1): 131–45.
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Files:: Cardelli, L, Kwiatkowska, MZ and Laurenti, L (2017) Natural Co...

(Preview, Version of record, pdf, 577.7KB, Terms of use)

Publisher copy:: 10.1007/s11047-017-9667-5

Authors

+ Cardelli, L More by this author

Institution:: University of Oxford
Division:: MPLS Division
Department:: Computer Science
Role:: Author

+ Kwiatkowska, M More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Computer Science
Oxford college:: Trinity College
Role:: Author

+ Laurenti, L More by this author

Institution:: University of Oxford
Division:: MPLS Division
Department:: Computer Science
Role:: Author

+ European Research Council More from this funder

Grant:: AdG VERIWARE

+ Royal Society More from this funder

Publisher:: Springer Netherlands
Journal:: Natural Computing More from this journal
Volume:: 17
Issue:: 1
Pages:: 131–145
Publication date:: 2017-12-08
Acceptance date:: 2017-11-29
DOI:: 10.1007/s11047-017-9667-5
EISSN:: 1572-9796
ISSN:: 1567-7818

Keywords:: quantitative reasoning

stochastic chemical reaction networks

discrete distributions
Pubs id:: pubs:809612
UUID:: uuid:7e6f1b5d-e4e3-4177-92a3-a70b14fdb778
Local pid:: pubs:809612
Source identifiers:: 809612
Deposit date:: 2017-12-06
ARK identifier:: ark:/29072/ora_7e6f1b5de4e3417792a3a70b14fdb778

Terms of use

Copyright holder:: Cardelli et al
Copyright date:: 2017
Notes:: Copyright © 2017 The Authors. This article is an open access publication
distributed under the terms of the Creative Commons Attribution 4.0 International License.

Licence:: CC Attribution (CC BY)

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