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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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

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

Citations

dimensions_citation
95 Dimensions

Readers on

mendeley
342 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.

Twitter Demographics

The data shown below were collected from the profiles of 23 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 342 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 292 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 89 26%
Researcher 89 26%
Student > Master 52 15%
Student > Bachelor 25 7%
Professor > Associate Professor 18 5%
Other 57 17%
Unknown 12 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 190 56%
Computer Science 43 13%
Biochemistry, Genetics and Molecular Biology 33 10%
Environmental Science 16 5%
Immunology and Microbiology 8 2%
Other 33 10%
Unknown 19 6%

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
#817,972
of 21,298,857 outputs
Outputs from BMC Bioinformatics
#66
of 6,905 outputs
Outputs of similar age
#4,161
of 142,731 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 10 outputs
Altmetric has tracked 21,298,857 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,905 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 99% 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 142,731 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 97% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them