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CANGS: a user-friendly utility for processing and analyzing 454 GS-FLX data in biodiversity studies

Overview of attention for article published in BMC Research Notes, January 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

q&a
1 Q&A thread

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
127 Mendeley
citeulike
4 CiteULike
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Title
CANGS: a user-friendly utility for processing and analyzing 454 GS-FLX data in biodiversity studies
Published in
BMC Research Notes, January 2010
DOI 10.1186/1756-0500-3-3
Pubmed ID
Authors

Ram Pandey, Viola Nolte, Christian Schlötterer

Abstract

Next generation sequencing (NGS) technologies have substantially increased the sequence output while the costs were dramatically reduced. In addition to the use in whole genome sequencing, the 454 GS-FLX platform is becoming a widely used tool for biodiversity surveys based on amplicon sequencing. In order to use NGS for biodiversity surveys, software tools are required, which perform quality control, trimming of the sequence reads, removal of PCR primers, and generation of input files for downstream analyses. A user-friendly software utility that carries out these steps is still lacking.

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
Germany 4 3%
Spain 3 2%
Italy 2 2%
Sweden 2 2%
France 2 2%
Canada 1 <1%
Mexico 1 <1%
Argentina 1 <1%
Other 3 2%
Unknown 102 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 38 30%
Student > Ph. D. Student 21 17%
Student > Master 14 11%
Professor > Associate Professor 13 10%
Professor 11 9%
Other 25 20%
Unknown 5 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 89 70%
Biochemistry, Genetics and Molecular Biology 11 9%
Environmental Science 4 3%
Immunology and Microbiology 4 3%
Computer Science 3 2%
Other 10 8%
Unknown 6 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 August 2010.
All research outputs
#1,403,704
of 3,628,714 outputs
Outputs from BMC Research Notes
#287
of 1,060 outputs
Outputs of similar age
#15,279
of 55,779 outputs
Outputs of similar age from BMC Research Notes
#9
of 34 outputs
Altmetric has tracked 3,628,714 research outputs across all sources so far. This one has received more attention than most of these and is in the 60th percentile.
So far Altmetric has tracked 1,060 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 72% 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 55,779 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 71% of its contemporaries.
We're also able to compare this research output to 34 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 73% of its contemporaries.