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TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets

Overview of attention for article published in BMC Bioinformatics, June 2010
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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1 X user
patent
2 patents

Citations

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202 Dimensions

Readers on

mendeley
269 Mendeley
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5 CiteULike
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Title
TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets
Published in
BMC Bioinformatics, June 2010
DOI 10.1186/1471-2105-11-341
Pubmed ID
Authors

Robert Schmieder, Yan Wei Lim, Forest Rohwer, Robert Edwards

Abstract

Sequencing metagenomes that were pre-amplified with primer-based methods requires the removal of the additional tag sequences from the datasets. The sequenced reads can contain deletions or insertions due to sequencing limitations, and the primer sequence may contain ambiguous bases. Furthermore, the tag sequence may be unavailable or incorrectly reported. Because of the potential for downstream inaccuracies introduced by unwanted sequence contaminations, it is important to use reliable tools for pre-processing sequence data.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 8 3%
France 3 1%
United States 3 1%
United Kingdom 2 <1%
Chile 1 <1%
Norway 1 <1%
Colombia 1 <1%
India 1 <1%
Sweden 1 <1%
Other 5 2%
Unknown 243 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 78 29%
Student > Ph. D. Student 50 19%
Student > Master 41 15%
Student > Bachelor 18 7%
Student > Doctoral Student 18 7%
Other 41 15%
Unknown 23 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 152 57%
Biochemistry, Genetics and Molecular Biology 38 14%
Computer Science 10 4%
Medicine and Dentistry 10 4%
Environmental Science 9 3%
Other 16 6%
Unknown 34 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 12 October 2023.
All research outputs
#6,905,877
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#2,684
of 7,234 outputs
Outputs of similar age
#31,451
of 93,825 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 71 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,234 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 gotten more attention than average, scoring higher than 61% 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 93,825 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 65% of its contemporaries.
We're also able to compare this research output to 71 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 54% of its contemporaries.