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Snpdat: Easy and rapid annotation of results from de novo snp discovery projects for model and non-model organisms

Overview of attention for article published in BMC Bioinformatics, February 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
8 X users
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
96 Mendeley
citeulike
1 CiteULike
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Title
Snpdat: Easy and rapid annotation of results from de novo snp discovery projects for model and non-model organisms
Published in
BMC Bioinformatics, February 2013
DOI 10.1186/1471-2105-14-45
Pubmed ID
Authors

Anthony G Doran, Christopher J Creevey

Abstract

Single nucleotide polymorphisms (SNPs) are the most abundant genetic variant found in vertebrates and invertebrates. SNP discovery has become a highly automated, robust and relatively inexpensive process allowing the identification of many thousands of mutations for model and non-model organisms. Annotating large numbers of SNPs can be a difficult and complex process. Many tools available are optimised for use with organisms densely sampled for SNPs, such as humans. There are currently few tools available that are species non-specific or support non-model organism data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 2 2%
Colombia 1 1%
Ghana 1 1%
Brazil 1 1%
Sweden 1 1%
Germany 1 1%
Spain 1 1%
Italy 1 1%
Other 2 2%
Unknown 82 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 25%
Student > Ph. D. Student 23 24%
Student > Master 10 10%
Student > Postgraduate 7 7%
Student > Doctoral Student 6 6%
Other 17 18%
Unknown 9 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 55%
Biochemistry, Genetics and Molecular Biology 18 19%
Computer Science 4 4%
Medicine and Dentistry 3 3%
Environmental Science 1 1%
Other 7 7%
Unknown 10 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 20 June 2017.
All research outputs
#4,433,373
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#1,668
of 7,454 outputs
Outputs of similar age
#46,730
of 289,623 outputs
Outputs of similar age from BMC Bioinformatics
#30
of 135 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 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 done well, scoring higher than 77% 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 289,623 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.