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Ultra-fast sequence clustering from similarity networks with SiLiX

Overview of attention for article published in BMC Bioinformatics, April 2011
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
239 Mendeley
citeulike
5 CiteULike
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Title
Ultra-fast sequence clustering from similarity networks with SiLiX
Published in
BMC Bioinformatics, April 2011
DOI 10.1186/1471-2105-12-116
Pubmed ID
Authors

Vincent Miele, Simon Penel, Laurent Duret

Abstract

The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this huge amount of sequences in order to build families of homologous sequences in a reasonable time.

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 239 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
France 4 2%
United Kingdom 3 1%
Sweden 2 <1%
Germany 2 <1%
China 2 <1%
Belgium 2 <1%
Tunisia 1 <1%
Switzerland 1 <1%
Other 1 <1%
Unknown 217 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 28%
Researcher 65 27%
Student > Master 28 12%
Student > Bachelor 18 8%
Professor > Associate Professor 13 5%
Other 39 16%
Unknown 10 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 145 61%
Biochemistry, Genetics and Molecular Biology 38 16%
Computer Science 19 8%
Chemistry 4 2%
Immunology and Microbiology 4 2%
Other 12 5%
Unknown 17 7%

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 02 October 2013.
All research outputs
#6,340,088
of 10,612,958 outputs
Outputs from BMC Bioinformatics
#2,909
of 4,170 outputs
Outputs of similar age
#74,263
of 147,851 outputs
Outputs of similar age from BMC Bioinformatics
#55
of 81 outputs
Altmetric has tracked 10,612,958 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,170 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 20th percentile – i.e., 20% 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 147,851 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.