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

Overview of attention for article published in Genome Biology (Online Edition), January 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

news
1 news outlet
twitter
21 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
140 Mendeley
citeulike
3 CiteULike
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Title
Temporal dynamics and transcriptional control using single-cell gene expression analysis
Published in
Genome Biology (Online Edition), January 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.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 140 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 128 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 31%
Researcher 37 26%
Professor > Associate Professor 11 8%
Student > Master 9 6%
Student > Bachelor 9 6%
Other 21 15%
Unknown 10 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 70 50%
Biochemistry, Genetics and Molecular Biology 20 14%
Computer Science 12 9%
Medicine and Dentistry 8 6%
Engineering 5 4%
Other 11 8%
Unknown 14 10%

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
#582,874
of 12,119,647 outputs
Outputs from Genome Biology (Online Edition)
#634
of 2,760 outputs
Outputs of similar age
#9,299
of 164,725 outputs
Outputs of similar age from Genome Biology (Online Edition)
#8
of 48 outputs
Altmetric has tracked 12,119,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,760 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. This one has done well, scoring higher than 76% 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 164,725 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 48 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.