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A comparative evaluation of sequence classification programs

Overview of attention for article published in BMC Bioinformatics, May 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
2 blogs
twitter
23 X users
patent
1 patent
peer_reviews
1 peer review site
wikipedia
2 Wikipedia pages
f1000
1 research highlight platform

Readers on

mendeley
346 Mendeley
citeulike
10 CiteULike
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Title
A comparative evaluation of sequence classification programs
Published in
BMC Bioinformatics, May 2012
DOI 10.1186/1471-2105-13-92
Pubmed ID
Authors

Adam L Bazinet, Michael P Cummings

Abstract

A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics). Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for 'barcoding genes' like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 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 346 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 4%
Brazil 6 2%
United Kingdom 4 1%
Canada 4 1%
Germany 3 <1%
Sweden 3 <1%
Netherlands 2 <1%
France 2 <1%
Japan 2 <1%
Other 10 3%
Unknown 296 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 89 26%
Student > Ph. D. Student 87 25%
Student > Master 54 16%
Student > Bachelor 23 7%
Professor > Associate Professor 18 5%
Other 58 17%
Unknown 17 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 190 55%
Computer Science 44 13%
Biochemistry, Genetics and Molecular Biology 32 9%
Environmental Science 18 5%
Engineering 8 2%
Other 29 8%
Unknown 25 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 38. 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 22 February 2022.
All research outputs
#930,223
of 23,172,045 outputs
Outputs from BMC Bioinformatics
#80
of 7,342 outputs
Outputs of similar age
#5,040
of 164,557 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 103 outputs
Altmetric has tracked 23,172,045 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,342 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 98% 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 164,557 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.