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Efficient proximal gradient algorithm for inference of differential gene networks

Overview of attention for article published in BMC Bioinformatics, May 2019
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1 X user

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26 Mendeley
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Article details
Title
Efficient proximal gradient algorithm for inference of differential gene networks
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2749-x
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 19%
Student > Ph. D. Student 4 15%
Student > Bachelor 3 12%
Other 2 8%
Student > Doctoral Student 2 8%
Other 4 15%
Unknown 6 23%
Readers by discipline
Readers by discipline Count As %
Computer Science 5 19%
Biochemistry, Genetics and Molecular Biology 4 15%
Mathematics 3 12%
Agricultural and Biological Sciences 3 12%
Engineering 2 8%
Other 2 8%
Unknown 7 27%
Attention Score in Context

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 05 May 2019.
All research outputs
#23,012,396
of 28,169,479 outputs
Outputs from BMC Bioinformatics
#6,851
of 7,920 outputs
Outputs of similar age
#283,641
of 367,471 outputs
Outputs of similar age from BMC Bioinformatics
#157
of 189 outputs
Altmetric has tracked 28,169,479 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,920 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 5th percentile – i.e., 5% 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 367,471 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.