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EDGAR: A software framework for the comparative analysis of prokaryotic genomes

Overview of attention for article published in BMC Bioinformatics, May 2009
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Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
340 Dimensions

Readers on

mendeley
333 Mendeley
citeulike
6 CiteULike
connotea
3 Connotea
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Title
EDGAR: A software framework for the comparative analysis of prokaryotic genomes
Published in
BMC Bioinformatics, May 2009
DOI 10.1186/1471-2105-10-154
Pubmed ID
Authors

Jochen Blom, Stefan P Albaum, Daniel Doppmeier, Alfred Pühler, Frank-Jörg Vorhölter, Martha Zakrzewski, Alexander Goesmann

Abstract

The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 333 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 3%
Brazil 6 2%
Germany 4 1%
Denmark 3 <1%
Spain 3 <1%
India 2 <1%
France 2 <1%
Finland 1 <1%
Sweden 1 <1%
Other 8 2%
Unknown 293 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 83 25%
Student > Ph. D. Student 76 23%
Student > Master 48 14%
Student > Bachelor 26 8%
Student > Doctoral Student 24 7%
Other 45 14%
Unknown 31 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 161 48%
Biochemistry, Genetics and Molecular Biology 66 20%
Computer Science 18 5%
Immunology and Microbiology 15 5%
Medicine and Dentistry 9 3%
Other 21 6%
Unknown 43 13%

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 01 September 2015.
All research outputs
#7,459,244
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#2,985
of 4,576 outputs
Outputs of similar age
#72,596
of 138,575 outputs
Outputs of similar age from BMC Bioinformatics
#33
of 55 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 30th percentile – i.e., 30% 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 138,575 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.