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Detection of viral sequence fragments of HIV-1 subfamilies yet unknown

Overview of attention for article published in BMC Bioinformatics, January 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
23 Mendeley
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Title
Detection of viral sequence fragments of HIV-1 subfamilies yet unknown
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-93
Pubmed ID
Authors

Thomas Unterthiner, Anne-Kathrin Schultz, Jan Bulla, Burkhard Morgenstern, Mario Stanke, Ingo Bulla

Abstract

Methods of determining whether or not any particular HIV-1 sequence stems - completely or in part - from some unknown HIV-1 subtype are important for the design of vaccines and molecular detection systems, as well as for epidemiological monitoring. Nevertheless, a single algorithm only, the Branching Index (BI), has been developed for this task so far. Moving along the genome of a query sequence in a sliding window, the BI computes a ratio quantifying how closely the query sequence clusters with a subtype clade. In its current version, however, the BI does not provide predicted boundaries of unknown fragments.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Sweden 1 4%
Brazil 1 4%
Unknown 20 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Professor 5 22%
Researcher 5 22%
Student > Master 3 13%
Unspecified 1 4%
Other 4 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 35%
Medicine and Dentistry 3 13%
Mathematics 3 13%
Computer Science 3 13%
Unspecified 1 4%
Other 4 17%
Unknown 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 27 July 2011.
All research outputs
#2,855,833
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#1,208
of 4,576 outputs
Outputs of similar age
#21,414
of 85,406 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 32 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 73% 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 85,406 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 74% of its contemporaries.
We're also able to compare this research output to 32 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 59% of its contemporaries.