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Transcriptomic and proteomic dynamics in the metabolism of a diazotrophic cyanobacterium, Cyanothece sp. PCC 7822 during a diurnal light–dark cycle

Overview of attention for article published in BMC Genomics, December 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
6 X users
facebook
3 Facebook pages

Citations

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19 Dimensions

Readers on

mendeley
66 Mendeley
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1 CiteULike
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Title
Transcriptomic and proteomic dynamics in the metabolism of a diazotrophic cyanobacterium, Cyanothece sp. PCC 7822 during a diurnal light–dark cycle
Published in
BMC Genomics, December 2014
DOI 10.1186/1471-2164-15-1185
Pubmed ID
Authors

David Welkie, Xiaohui Zhang, Meng Lye Markillie, Ronald Taylor, Galya Orr, Jon Jacobs, Ketaki Bhide, Jyothi Thimmapuram, Marina Gritsenko, Hugh Mitchell, Richard D Smith, Louis A Sherman

Abstract

Cyanothece sp. PCC 7822 is an excellent cyanobacterial model organism with great potential to be applied as a biocatalyst for the production of high value compounds. Like other unicellular diazotrophic cyanobacterial species, it has a tightly regulated metabolism synchronized to the light-dark cycle. Utilizing transcriptomic and proteomic methods, we quantified the relationships between transcription and translation underlying central and secondary metabolism in response to nitrogen free, 12 hour light and 12 hour dark conditions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 2%
Unknown 65 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 26%
Researcher 11 17%
Student > Master 11 17%
Student > Bachelor 6 9%
Student > Doctoral Student 2 3%
Other 6 9%
Unknown 13 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 41%
Biochemistry, Genetics and Molecular Biology 13 20%
Chemistry 2 3%
Computer Science 2 3%
Engineering 2 3%
Other 6 9%
Unknown 14 21%
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 15 August 2015.
All research outputs
#7,345,736
of 23,881,329 outputs
Outputs from BMC Genomics
#3,321
of 10,793 outputs
Outputs of similar age
#97,983
of 358,160 outputs
Outputs of similar age from BMC Genomics
#70
of 249 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 67% 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 358,160 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 71% of its contemporaries.
We're also able to compare this research output to 249 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 68% of its contemporaries.