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Cited by 447

The DOI matches its Crossref record; 419 of the 419 references it cites were found in a registry or an index.

Chemistries for DNA Nanotechnology

Madsen, Mikael, Gothelf, Kurt V.·2019·Chemical Reviews

Abstract

The predictable nature of DNA interactions enables the programmable assembly of highly advanced 2D and 3D DNA structures of nanoscale dimensions. The access to ever larger and more complex structures has been achieved through decades of work on developing structural design principles. Concurrently, an increased focus has emerged on the applications of DNA nanostructures. In its nature, DNA is chemically inert and nanostructures based on unmodified DNA mostly lack function. However, functionality can be obtained through chemical modification of DNA nanostructures and the opportunities are endless. In this review, we discuss methodology for chemical functionalization of DNA nanostructures and provide examples of how this is being used to create functional nanodevices and make DNA nanostructures more applicable. We aim to encourage researchers to adopt chemical modifications as part of their work in DNA nanotechnology and inspire chemists to address current challenges and opportunities within the field.

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Crossref · 10.1021/acs.chemrev.8b00570

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Metadata

Authors
Madsen, M., & Gothelf, K. V.
Venue
Chemical Reviews
Published
2019-02-04
Volume
119
Issue
10
Pages
6384-6458
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2913121738
Cited by
447
References
419
FWCI
4.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Chemistries for DNA Nanotechnology. https://app.cochat.ai/papers/10.1021/acs.chemrev.8b00570
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Madsen, M., & Gothelf, K. V. (2019). Chemistries for DNA Nanotechnology. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.8b00570

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.