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LAVA: An Open-Source Approach To Designing LAMP (Loop-Mediated Isothermal Amplification) DNA Signatures

Overview of attention for article published in BMC Bioinformatics, June 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

patent
4 patents
wikipedia
5 Wikipedia pages

Citations

dimensions_citation
60 Dimensions

Readers on

mendeley
206 Mendeley
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Title
LAVA: An Open-Source Approach To Designing LAMP (Loop-Mediated Isothermal Amplification) DNA Signatures
Published in
BMC Bioinformatics, June 2011
DOI 10.1186/1471-2105-12-240
Pubmed ID
Authors

Clinton Torres, Elizabeth A Vitalis, Brian R Baker, Shea N Gardner, Marisa W Torres, John M Dzenitis

Abstract

We developed an extendable open-source Loop-mediated isothermal AMPlification (LAMP) signature design program called LAVA (LAMP Assay Versatile Analysis). LAVA was created in response to limitations of existing LAMP signature programs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 206 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 2 <1%
Germany 1 <1%
Switzerland 1 <1%
Malaysia 1 <1%
France 1 <1%
Kenya 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Ukraine 1 <1%
Other 4 2%
Unknown 192 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 23%
Student > Ph. D. Student 34 17%
Student > Master 30 15%
Student > Bachelor 15 7%
Professor > Associate Professor 10 5%
Other 38 18%
Unknown 32 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 76 37%
Biochemistry, Genetics and Molecular Biology 46 22%
Medicine and Dentistry 15 7%
Immunology and Microbiology 9 4%
Veterinary Science and Veterinary Medicine 7 3%
Other 18 9%
Unknown 35 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 24 January 2023.
All research outputs
#4,906,861
of 23,578,918 outputs
Outputs from BMC Bioinformatics
#1,854
of 7,398 outputs
Outputs of similar age
#22,478
of 102,151 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 99 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,398 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 73% of its peers.
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 102,151 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.