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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2017
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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. |
format | Online Article Text |
id | pubmed-5856912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
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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