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Detecting the limits of regulatory element conservation and divergence estimation using pairwise and multiple alignments

Overview of attention for article published in BMC Bioinformatics, August 2006
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

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2 X users
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1 Q&A thread

Citations

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44 Dimensions

Readers on

mendeley
49 Mendeley
citeulike
9 CiteULike
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1 Connotea
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Title
Detecting the limits of regulatory element conservation and divergence estimation using pairwise and multiple alignments
Published in
BMC Bioinformatics, August 2006
DOI 10.1186/1471-2105-7-376
Pubmed ID
Authors

Daniel A Pollard, Alan M Moses, Venky N Iyer, Michael B Eisen

Abstract

Molecular evolutionary studies of noncoding sequences rely on multiple alignments. Yet how multiple alignment accuracy varies across sequence types, tree topologies, divergences and tools, and further how this variation impacts specific inferences, remains unclear.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 10%
Chile 2 4%
Spain 2 4%
Italy 1 2%
Indonesia 1 2%
Norway 1 2%
Poland 1 2%
Unknown 36 73%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Researcher 14 29%
Professor > Associate Professor 7 14%
Student > Bachelor 2 4%
Professor 2 4%
Other 7 14%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 65%
Biochemistry, Genetics and Molecular Biology 6 12%
Computer Science 6 12%
Physics and Astronomy 1 2%
Unknown 4 8%
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 13 November 2012.
All research outputs
#7,959,162
of 25,371,288 outputs
Outputs from BMC Bioinformatics
#2,886
of 7,692 outputs
Outputs of similar age
#29,861
of 91,666 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 32 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,692 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 60% 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 91,666 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 66% 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 56% of its contemporaries.