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Regularized estimation of large-scale gene association networks using graphical Gaussian models

Overview of attention for article published in BMC Bioinformatics, November 2009
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Mentioned by

policy
1 policy source

Readers on

mendeley
186 Mendeley
citeulike
4 CiteULike
connotea
2 Connotea
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Title
Regularized estimation of large-scale gene association networks using graphical Gaussian models
Published in
BMC Bioinformatics, November 2009
DOI 10.1186/1471-2105-10-384
Pubmed ID
Authors

Nicole Krämer, Juliane Schäfer, Anne-Laure Boulesteix

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 186 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
Italy 1 <1%
Taiwan 1 <1%
United Kingdom 1 <1%
China 1 <1%
Belgium 1 <1%
Unknown 174 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 27%
Student > Ph. D. Student 46 25%
Student > Master 21 11%
Professor > Associate Professor 10 5%
Student > Doctoral Student 9 5%
Other 28 15%
Unknown 22 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 20%
Computer Science 28 15%
Psychology 21 11%
Mathematics 20 11%
Medicine and Dentistry 11 6%
Other 36 19%
Unknown 32 17%
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 01 January 2017.
All research outputs
#7,935,898
of 23,885,338 outputs
Outputs from BMC Bioinformatics
#3,102
of 7,485 outputs
Outputs of similar age
#50,302
of 171,337 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 48 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,485 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 50% 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 171,337 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.