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Detection of second-line drug resistance in Mycobacterium tuberculosis using oligonucleotide microarrays

Overview of attention for article published in BMC Infectious Diseases, May 2013
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1 tweeter
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1 Facebook page

Citations

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35 Dimensions

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62 Mendeley
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Title
Detection of second-line drug resistance in Mycobacterium tuberculosis using oligonucleotide microarrays
Published in
BMC Infectious Diseases, May 2013
DOI 10.1186/1471-2334-13-240
Pubmed ID
Authors

Danila V Zimenkov, Olga V Antonova, Alexey V Kuz’min, Yulia D Isaeva, Ludmila Y Krylova, Sergey A Popov, Alexander S Zasedatelev, Vladimir M Mikhailovich, Dmitry A Gryadunov

Abstract

The steady rise in the spread of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) requires rapid and reliable methods to identify resistant strains. The current molecular methods to detect MTB resistance to second-line drugs either do not cover an extended spectrum of mutations to be identified or are not easily implemented in clinical laboratories. A rapid molecular technique for the detection of resistance to second-line drugs in M. tuberculosis has been developed using hybridisation analysis on microarrays.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Germany 1 2%
Unknown 60 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Ph. D. Student 10 16%
Student > Master 9 15%
Student > Postgraduate 7 11%
Other 6 10%
Other 8 13%
Unknown 11 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 27%
Medicine and Dentistry 12 19%
Biochemistry, Genetics and Molecular Biology 7 11%
Immunology and Microbiology 5 8%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Other 5 8%
Unknown 13 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2013.
All research outputs
#13,174,468
of 16,578,610 outputs
Outputs from BMC Infectious Diseases
#4,273
of 5,982 outputs
Outputs of similar age
#115,088
of 160,310 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
Altmetric has tracked 16,578,610 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,982 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 160,310 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them