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Pattern Transformation with DNA Circuits

Readily programmable chemical networks are important tools as the scope of chemistry expands from individual molecules to larger molecular systems. While many complex systems have been constructed using conventional organic and inorganic chemistry, the programmability of biological molecules such as...

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Detalles Bibliográficos
Autores principales: Chirieleison, Steven M., Allen, Peter B., Simpson, Zack B., Ellington, Andrew D., Chen, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3970425/
https://www.ncbi.nlm.nih.gov/pubmed/24256862
http://dx.doi.org/10.1038/nchem.1764
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author Chirieleison, Steven M.
Allen, Peter B.
Simpson, Zack B.
Ellington, Andrew D.
Chen, Xi
author_facet Chirieleison, Steven M.
Allen, Peter B.
Simpson, Zack B.
Ellington, Andrew D.
Chen, Xi
author_sort Chirieleison, Steven M.
collection PubMed
description Readily programmable chemical networks are important tools as the scope of chemistry expands from individual molecules to larger molecular systems. While many complex systems have been constructed using conventional organic and inorganic chemistry, the programmability of biological molecules such as nucleic acids allows for precise, high-throughput, and automated design, as well as simple, rapid, and robust implementation. Here we show that systematic and quantitative control over the diffusivity and reactivity of DNA molecules yields highly programmable chemical reaction networks (CRNs) that execute at the macroscale. In particular, we design and implement non-enzymatic DNA circuits capable of performing pattern transformation algorithms such as edge detection. We also show that it is possible to fine-tune and multiplex such circuits. We believe these strategies will provide programmable platforms for prototyping CRNs, for discovering bottom-up construction principles, and for generating patterns in materials.
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spelling pubmed-39704252014-06-01 Pattern Transformation with DNA Circuits Chirieleison, Steven M. Allen, Peter B. Simpson, Zack B. Ellington, Andrew D. Chen, Xi Nat Chem Article Readily programmable chemical networks are important tools as the scope of chemistry expands from individual molecules to larger molecular systems. While many complex systems have been constructed using conventional organic and inorganic chemistry, the programmability of biological molecules such as nucleic acids allows for precise, high-throughput, and automated design, as well as simple, rapid, and robust implementation. Here we show that systematic and quantitative control over the diffusivity and reactivity of DNA molecules yields highly programmable chemical reaction networks (CRNs) that execute at the macroscale. In particular, we design and implement non-enzymatic DNA circuits capable of performing pattern transformation algorithms such as edge detection. We also show that it is possible to fine-tune and multiplex such circuits. We believe these strategies will provide programmable platforms for prototyping CRNs, for discovering bottom-up construction principles, and for generating patterns in materials. 2013-09-29 2013-12 /pmc/articles/PMC3970425/ /pubmed/24256862 http://dx.doi.org/10.1038/nchem.1764 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Chirieleison, Steven M.
Allen, Peter B.
Simpson, Zack B.
Ellington, Andrew D.
Chen, Xi
Pattern Transformation with DNA Circuits
title Pattern Transformation with DNA Circuits
title_full Pattern Transformation with DNA Circuits
title_fullStr Pattern Transformation with DNA Circuits
title_full_unstemmed Pattern Transformation with DNA Circuits
title_short Pattern Transformation with DNA Circuits
title_sort pattern transformation with dna circuits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3970425/
https://www.ncbi.nlm.nih.gov/pubmed/24256862
http://dx.doi.org/10.1038/nchem.1764
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