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PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data

Overview of attention for article published in Genome Biology, February 2009
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Mentioned by

patent
1 patent

Citations

dimensions_citation
233 Dimensions

Readers on

mendeley
352 Mendeley
citeulike
24 CiteULike
connotea
5 Connotea
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Title
PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
Published in
Genome Biology, February 2009
DOI 10.1186/gb-2009-10-2-r23
Pubmed ID
Authors

Jan O Korbel, Alexej Abyzov, Xinmeng Jasmine Mu, Nicholas Carriero, Philip Cayting, Zhengdong Zhang, Michael Snyder, Mark B Gerstein

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 352 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 3%
Germany 7 2%
United Kingdom 7 2%
Netherlands 3 <1%
France 3 <1%
Brazil 2 <1%
Belgium 2 <1%
Italy 2 <1%
Spain 2 <1%
Other 6 2%
Unknown 306 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 110 31%
Student > Ph. D. Student 86 24%
Student > Master 30 9%
Professor > Associate Professor 26 7%
Professor 18 5%
Other 54 15%
Unknown 28 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 198 56%
Biochemistry, Genetics and Molecular Biology 41 12%
Computer Science 33 9%
Medicine and Dentistry 14 4%
Mathematics 8 2%
Other 23 7%
Unknown 35 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 December 2019.
All research outputs
#8,535,684
of 25,374,917 outputs
Outputs from Genome Biology
#3,489
of 4,467 outputs
Outputs of similar age
#38,802
of 109,795 outputs
Outputs of similar age from Genome Biology
#10
of 20 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 14th percentile – i.e., 14% 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 109,795 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.