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Programming discrete distributions with chemical reaction networks

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 [Formula: see text] , with [Formula: see text] . Mor...

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Detalles Bibliográficos
Autores principales: Cardelli, Luca, Kwiatkowska, Marta, Laurenti, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856912/
https://www.ncbi.nlm.nih.gov/pubmed/29576758
http://dx.doi.org/10.1007/s11047-017-9667-5
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author Cardelli, Luca
Kwiatkowska, Marta
Laurenti, Luca
author_facet Cardelli, Luca
Kwiatkowska, Marta
Laurenti, Luca
author_sort Cardelli, Luca
collection PubMed
description 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 [Formula: see text] , with [Formula: see text] . Moreover, any distribution with countable infinite support can be approximated with arbitrarily small error under the [Formula: see text] 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.
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spelling pubmed-58569122018-03-21 Programming discrete distributions with chemical reaction networks Cardelli, Luca Kwiatkowska, Marta Laurenti, Luca Nat Comput Article 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 [Formula: see text] , with [Formula: see text] . Moreover, any distribution with countable infinite support can be approximated with arbitrarily small error under the [Formula: see text] 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. Springer Netherlands 2017-12-08 2018 /pmc/articles/PMC5856912/ /pubmed/29576758 http://dx.doi.org/10.1007/s11047-017-9667-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Cardelli, Luca
Kwiatkowska, Marta
Laurenti, Luca
Programming discrete distributions with chemical reaction networks
title Programming discrete distributions with chemical reaction networks
title_full Programming discrete distributions with chemical reaction networks
title_fullStr Programming discrete distributions with chemical reaction networks
title_full_unstemmed Programming discrete distributions with chemical reaction networks
title_short Programming discrete distributions with chemical reaction networks
title_sort programming discrete distributions with chemical reaction networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856912/
https://www.ncbi.nlm.nih.gov/pubmed/29576758
http://dx.doi.org/10.1007/s11047-017-9667-5
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