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Cited by 587

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Rolling Circle Amplification: Applications in Nanotechnology and Biodetection with Functional Nucleic Acids

Zhao, Weian, Ali, M. Monsur, Brook, Michael A., Li, Yingfu·2008·Angewandte Chemie International Edition

Abstract

Rolling circle amplification (RCA) is an isothermal, enzymatic process mediated by certain DNA polymerases in which long single‐stranded (ss) DNA molecules are synthesized on a short circular ssDNA template by using a single DNA primer. A method traditionally used for ultrasensitive DNA detection in areas of genomics and diagnostics, RCA has been used more recently to generate large‐scale DNA templates for the creation of periodic nanoassemblies. Various RCA strategies have also been developed for the production of repetitive sequences of DNA aptamers and DNAzymes as detection platforms for small molecules and proteins. In this way, RCA is rapidly becoming a highly versatile DNA amplification tool with wide‐ranging applications in genomics, proteomics, diagnosis, biosensing, drug discovery, and nanotechnology.

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Crossref · 10.1002/anie.200705982

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Metadata

Authors
Zhao, W., Ali, M. M., Brook, M. A., & Li, Y.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2008-08-04
Volume
47
Issue
34
Pages
6330-6337
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2050387685
Cited by
587
References
3
FWCI
7.57
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Rolling Circle Amplification: Applications in Nanotechnology and Biodetection with Functional Nucleic Acids. https://app.cochat.ai/papers/10.1002/anie.200705982
The paper
Zhao, W., Ali, M. M., Brook, M. A., & Li, Y. (2008). Rolling Circle Amplification: Applications in Nanotechnology and Biodetection with Functional Nucleic Acids. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200705982

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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.