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Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

Overview of attention for article published in BMC Genomics, June 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
2 X users
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
15 Mendeley
Title
Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty
Published in
BMC Genomics, June 2019
DOI 10.1186/s12864-019-5720-3
Pubmed ID
Authors

Ehsan Hajiramezanali, Mahdi Imani, Ulisses Braga-Neto, Xiaoning Qian, Edward R. Dougherty

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Researcher 1 7%
Student > Postgraduate 1 7%
Student > Master 1 7%
Unknown 8 53%
Readers by discipline Count As %
Computer Science 2 13%
Arts and Humanities 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Psychology 1 7%
Physics and Astronomy 1 7%
Other 1 7%
Unknown 8 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 November 2023.
All research outputs
#6,593,026
of 23,323,574 outputs
Outputs from BMC Genomics
#2,936
of 10,742 outputs
Outputs of similar age
#120,465
of 354,479 outputs
Outputs of similar age from BMC Genomics
#73
of 248 outputs
Altmetric has tracked 23,323,574 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 10,742 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 71% 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 354,479 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 65% of its contemporaries.
We're also able to compare this research output to 248 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.