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Temporal dynamics and transcriptional control using single-cell gene expression analysis

Overview of attention for article published in Genome Biology, December 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

news
1 news outlet
twitter
21 X users
googleplus
1 Google+ user

Citations

dimensions_citation
43 Dimensions

Readers on

mendeley
148 Mendeley
citeulike
3 CiteULike
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Title
Temporal dynamics and transcriptional control using single-cell gene expression analysis
Published in
Genome Biology, December 2013
DOI 10.1186/gb-2013-14-10-r118
Pubmed ID
Authors

Tsukasa Kouno, Michiel de Hoon, Jessica C Mar, Yasuhiro Tomaru, Mitsuoki Kawano, Piero Carninci, Harukazu Suzuki, Yoshihide Hayashizaki, Jay W Shin

Abstract

Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event.

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 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 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 6%
United Kingdom 1 <1%
China 1 <1%
Italy 1 <1%
Unknown 136 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 28%
Researcher 36 24%
Professor > Associate Professor 11 7%
Student > Bachelor 10 7%
Student > Master 9 6%
Other 21 14%
Unknown 19 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 67 45%
Biochemistry, Genetics and Molecular Biology 19 13%
Computer Science 15 10%
Medicine and Dentistry 7 5%
Engineering 5 3%
Other 12 8%
Unknown 23 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 09 November 2017.
All research outputs
#1,669,267
of 25,374,917 outputs
Outputs from Genome Biology
#1,367
of 4,467 outputs
Outputs of similar age
#18,197
of 320,160 outputs
Outputs of similar age from Genome Biology
#27
of 97 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 has gotten more attention than average, scoring higher than 69% 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 320,160 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 97 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 72% of its contemporaries.