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Cited by 1,242

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Engineering Entropy-Driven Reactions and Networks Catalyzed by DNA

Zhang, David Yu, Turberfield, Andrew J., Yurke, Bernard, Winfree, Erik·2007·Science

Abstract

Artificial biochemical circuits are likely to play as large a role in biological engineering as electrical circuits have played in the engineering of electromechanical devices. Toward that end, nucleic acids provide a designable substrate for the regulation of biochemical reactions. However, it has been difficult to incorporate signal amplification components. We introduce a design strategy that allows a specified input oligonucleotide to catalyze the release of a specified output oligonucleotide, which in turn can serve as a catalyst for other reactions. This reaction, which is driven forward by the configurational entropy of the released molecule, provides an amplifying circuit element that is simple, fast, modular, composable, and robust. We have constructed and characterized several circuits that amplify nucleic acid signals, including a feedforward cascade with quadratic kinetics and a positive feedback circuit with exponential growth kinetics.

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Crossref · 10.1126/science.1148532

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Metadata

Authors
Zhang, D. Y., Turberfield, A. J., Yurke, B., & Winfree, E.
Venue
Science
Published
2007-11-16
Volume
318
Issue
5853
Pages
1121-1125
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2050630660
Cited by
1,242
References
1
FWCI
8.50
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Engineering Entropy-Driven Reactions and Networks Catalyzed by DNA. https://app.cochat.ai/papers/10.1126/science.1148532
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Zhang, D. Y., Turberfield, A. J., Yurke, B., & Winfree, E. (2007). Engineering Entropy-Driven Reactions and Networks Catalyzed by DNA. Science. https://doi.org/10.1126/science.1148532

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.