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EggLib: processing, analysis and simulation tools for population genetics and genomics

Overview of attention for article published in BMC Genomic Data, April 2012
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
143 Dimensions

Readers on

mendeley
157 Mendeley
citeulike
3 CiteULike
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Title
EggLib: processing, analysis and simulation tools for population genetics and genomics
Published in
BMC Genomic Data, April 2012
DOI 10.1186/1471-2156-13-27
Pubmed ID
Authors

Stéphane De Mita, Mathieu Siol

Abstract

With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 4%
France 4 3%
Sweden 3 2%
United Kingdom 2 1%
Germany 1 <1%
South Africa 1 <1%
Portugal 1 <1%
Romania 1 <1%
Chile 1 <1%
Other 2 1%
Unknown 135 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 27%
Student > Ph. D. Student 39 25%
Student > Master 24 15%
Professor 11 7%
Professor > Associate Professor 9 6%
Other 18 11%
Unknown 13 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 106 68%
Biochemistry, Genetics and Molecular Biology 19 12%
Environmental Science 4 3%
Computer Science 4 3%
Earth and Planetary Sciences 3 2%
Other 6 4%
Unknown 15 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 June 2012.
All research outputs
#16,047,334
of 25,374,647 outputs
Outputs from BMC Genomic Data
#548
of 1,204 outputs
Outputs of similar age
#105,149
of 173,991 outputs
Outputs of similar age from BMC Genomic Data
#10
of 22 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 50% 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 173,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 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 54% of its contemporaries.