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Cited by 889

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Loop-mediated isothermal amplification (LAMP): principle, features, and future prospects

Notomi, Tsugunori, Mori, Yasuyoshi, Tomita, Norihiro, Kanda, Hidetoshi·2015·Journal of Microbiology

Abstract

Loop-mediated isothermal amplification (LAMP), a newly developed gene amplification method, combines rapidity, simplicity, and high specificity. Several tests have been developed based on this method, and simplicity is maintained throughout all steps, from extraction of nucleic acids to detection of amplification. In the LAMP reaction, samples are amplified at a fixed temperature through a repetition of two types of elongation reactions occurring at the loop regions: self-elongation of templates from the stem loop structure formed at the 3'-terminal and the binding and elongation of new primers to the loop region. The LAMP reaction has a wide range of possible applications, including point-of-care testing, genetic testing in resource-poor settings (such as in developing countries), and rapid testing of food products and environmental samples.

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Metadata

Authors
Notomi, T., Mori, Y., Tomita, N., & Kanda, H.
Venue
Journal of Microbiology
Published
2015-01
Volume
53
Issue
1
Pages
1-5
ISSN
  • 1225-8873 (ISSN-L)
  • 1976-3794
OpenAlex
W2063533401
Cited by
889
References
12
FWCI
24.38
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Loop-mediated isothermal amplification (LAMP): principle, features, and future prospects. https://app.cochat.ai/papers/10.1007/s12275-015-4656-9
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Notomi, T., Mori, Y., Tomita, N., & Kanda, H. (2015). Loop-mediated isothermal amplification (LAMP): principle, features, and future prospects. Journal of Microbiology. https://doi.org/10.1007/s12275-015-4656-9

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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.