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Deep Sequencing Reveals Novel MicroRNAs and Regulation of MicroRNA Expression during Cell Senescence

Overview of attention for article published in PLOS ONE, May 2011
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1 X user

Citations

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4 CiteULike
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Title
Deep Sequencing Reveals Novel MicroRNAs and Regulation of MicroRNA Expression during Cell Senescence
Published in
PLOS ONE, May 2011
DOI 10.1371/journal.pone.0020509
Pubmed ID
Authors

Joseph M. Dhahbi, Hani Atamna, Dario Boffelli, Wendy Magis, Stephen R. Spindler, David I. K. Martin

Abstract

In cell senescence, cultured cells cease proliferating and acquire aberrant gene expression patterns. MicroRNAs (miRNAs) modulate gene expression through translational repression or mRNA degradation and have been implicated in senescence. We used deep sequencing to carry out a comprehensive survey of miRNA expression and involvement in cell senescence. Informatic analysis of small RNA sequence datasets from young and senescent IMR90 human fibroblasts identifies many miRNAs that are regulated (either up or down) with cell senescence. Comparison with mRNA expression profiles reveals potential mRNA targets of these senescence-regulated miRNAs. The target mRNAs are enriched for genes involved in biological processes associated with cell senescence. This result greatly extends existing information on the role of miRNAs in cell senescence and is consistent with miRNAs having a causal role in the process.

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The data shown below were collected from the profile of 1 X user 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Germany 2 2%
Denmark 2 2%
Brazil 2 2%
Austria 1 <1%
Unknown 117 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 28%
Student > Ph. D. Student 33 26%
Student > Master 13 10%
Professor > Associate Professor 9 7%
Professor 5 4%
Other 17 13%
Unknown 14 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 54%
Biochemistry, Genetics and Molecular Biology 21 17%
Medicine and Dentistry 10 8%
Veterinary Science and Veterinary Medicine 3 2%
Computer Science 2 2%
Other 8 6%
Unknown 14 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 December 2012.
All research outputs
#18,313,878
of 22,675,759 outputs
Outputs from PLOS ONE
#153,821
of 193,562 outputs
Outputs of similar age
#95,895
of 112,117 outputs
Outputs of similar age from PLOS ONE
#1,400
of 1,685 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,562 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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