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Detecting long tandem duplications in genomic sequences

Overview of attention for article published in BMC Bioinformatics, May 2012
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1 tweeter

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56 Mendeley
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2 CiteULike
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Title
Detecting long tandem duplications in genomic sequences
Published in
BMC Bioinformatics, May 2012
DOI 10.1186/1471-2105-13-83
Pubmed ID
Authors

Eric Audemard, Thomas Schiex, Thomas Faraut

Abstract

Detecting duplication segments within completely sequenced genomes provides valuable information to address genome evolution and in particular the important question of the emergence of novel functions. The usual approach to gene duplication detection, based on all-pairs protein gene comparisons, provides only a restricted view of duplication.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Taiwan 1 2%
Sri Lanka 1 2%
Mexico 1 2%
Russia 1 2%
United Kingdom 1 2%
Unknown 49 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 39%
Student > Ph. D. Student 10 18%
Student > Master 6 11%
Professor > Associate Professor 3 5%
Professor 3 5%
Other 9 16%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 61%
Biochemistry, Genetics and Molecular Biology 10 18%
Computer Science 3 5%
Medicine and Dentistry 2 4%
Unspecified 1 2%
Other 3 5%
Unknown 3 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 May 2012.
All research outputs
#9,906,143
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,815
of 4,576 outputs
Outputs of similar age
#83,767
of 118,352 outputs
Outputs of similar age from BMC Bioinformatics
#34
of 42 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 118,352 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.