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Fast Bayesian inference for gene regulatory networks using ScanBMA

Overview of attention for article published in BMC Systems Biology, April 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
72 Dimensions

Readers on

mendeley
114 Mendeley
citeulike
1 CiteULike
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Title
Fast Bayesian inference for gene regulatory networks using ScanBMA
Published in
BMC Systems Biology, April 2014
DOI 10.1186/1752-0509-8-47
Pubmed ID
Authors

William Chad Young, Adrian E Raftery, Ka Yee Yeung

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
United Kingdom 2 2%
Brazil 1 <1%
Cuba 1 <1%
India 1 <1%
Unknown 107 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 32%
Researcher 22 19%
Student > Master 18 16%
Student > Doctoral Student 7 6%
Other 7 6%
Other 17 15%
Unknown 7 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 35%
Computer Science 28 25%
Biochemistry, Genetics and Molecular Biology 16 14%
Mathematics 7 6%
Engineering 6 5%
Other 10 9%
Unknown 7 6%
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 19 May 2020.
All research outputs
#7,656,930
of 23,310,485 outputs
Outputs from BMC Systems Biology
#315
of 1,143 outputs
Outputs of similar age
#74,882
of 227,454 outputs
Outputs of similar age from BMC Systems Biology
#7
of 28 outputs
Altmetric has tracked 23,310,485 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 1,143 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 63% 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 227,454 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 54% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.