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Widespread uncoupling between transcriptome and translatome variations after a stimulus in mammalian cells

Overview of attention for article published in BMC Genomics, June 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

Mentioned by

twitter
6 tweeters
patent
1 patent

Citations

dimensions_citation
102 Dimensions

Readers on

mendeley
138 Mendeley
citeulike
1 CiteULike
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Title
Widespread uncoupling between transcriptome and translatome variations after a stimulus in mammalian cells
Published in
BMC Genomics, June 2012
DOI 10.1186/1471-2164-13-220
Pubmed ID
Authors

Toma Tebaldi, Angela Re, Gabriella Viero, Ilaria Pegoretti, Andrea Passerini, Enrico Blanzieri, Alessandro Quattrone

Abstract

The classical view on eukaryotic gene expression proposes the scheme of a forward flow for which fluctuations in mRNA levels upon a stimulus contribute to determine variations in mRNA availability for translation. Here we address this issue by simultaneously profiling with microarrays the total mRNAs (the transcriptome) and the polysome-associated mRNAs (the translatome) after EGF treatment of human cells, and extending the analysis to other 19 different transcriptome/translatome comparisons in mammalian cells following different stimuli or undergoing cell programs.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
Germany 1 <1%
Italy 1 <1%
Australia 1 <1%
Sweden 1 <1%
South Africa 1 <1%
Japan 1 <1%
United States 1 <1%
Unknown 130 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 25%
Student > Ph. D. Student 32 23%
Student > Master 19 14%
Student > Bachelor 12 9%
Student > Doctoral Student 7 5%
Other 20 14%
Unknown 13 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 65 47%
Biochemistry, Genetics and Molecular Biology 31 22%
Neuroscience 7 5%
Medicine and Dentistry 6 4%
Computer Science 2 1%
Other 7 5%
Unknown 20 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 26 January 2017.
All research outputs
#5,037,367
of 21,298,857 outputs
Outputs from BMC Genomics
#2,053
of 10,263 outputs
Outputs of similar age
#32,672
of 143,426 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 21,298,857 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,263 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 79% 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 143,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them