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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 Applied Microbiology...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
Applied Microbiology and Biotechnology
Article . 2012 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Antimicrobials, drug discovery, and genome mining

Authors: R J, Scheffler; S, Colmer; H, Tynan; A L, Demain; V P, Gullo;

Antimicrobials, drug discovery, and genome mining

Abstract

Over the years, antibiotics have provided an effective treatment for a number of microbial diseases. However recently, there has been an increase in resistant microorganisms that have adapted to our current antibiotics. One of the most dangerous pathogens is methicillin-resistant Staphylococcus aureus (MRSA). With the rise in the cases of MRSA and other resistant pathogens such as vancomycin-resistant Staphylococcus aureus, the need for new antibiotics increases every day. Many challenges face the discovery and development of new antibiotics, making it difficult for these new drugs to reach the market, especially since many of the pharmaceutical companies have stopped searching for antibiotics. With the advent of genome sequencing, new antibiotics are being found by the techniques of genome mining, offering hope for the future.

Related Organizations
Keywords

Anti-Infective Agents, Drug Discovery, Drug Resistance, Bacterial, Computational Biology, Data Mining, Humans, Bacterial Infections, Genomics

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    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!
83
Top 10%
Top 10%
Top 10%
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