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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Nature Reviews Micro...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Nature Reviews Microbiology
Article . 2004 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
Nature Reviews Microbiology
Article . 2004
Data sources: Europe PubMed Central
https://dx.doi.org/10.1038/nrm...
Article
Data sources: Microsoft Academic Graph
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Predicting the evolution of antibiotic resistance genes

descriptionPublicationkeyboard_double_arrow_right Article 01 May 2004 English Publisher:Springer Science and Business Media LLCJournal:Nature Reviews Microbiology, volume 2, pages 430-435 (issn: 1740-1526, eissn: 1740-1534, Copyright policy )
Authors: Barry G, Hall;

doi: 10.1038/nrmicro888

pmid: 15100696

Predicting the evolution of antibiotic resistance genes

Abstract

Antibiotic resistance is thought to evolve rapidly in response to antibiotic use. At present, we lack effective tools to assess how rapidly existing resistance genes are likely to evolve to yield resistance to newly introduced drugs. To address this problem, a method has been developed for in vitro evolution experiments to help predict how long it will take antibiotic resistance to arise — potentially allowing informed decisions about usage to be made.

Related Organizations
Keywords

Drug Resistance, Multiple, Bacterial, Animals, Humans, Bacterial Infections, Directed Molecular Evolution, Selection, Genetic, Anti-Bacterial Agents

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 94
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 10%
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
94
Top 10%
Top 10%
Top 10%
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