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Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells

Overview of attention for article published in Genome Research, February 2008
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
1 news outlet
twitter
3 X users
patent
20 patents
wikipedia
2 Wikipedia pages

Readers on

mendeley
768 Mendeley
citeulike
21 CiteULike
connotea
8 Connotea
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Title
Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells
Published in
Genome Research, February 2008
DOI 10.1101/gr.7179508
Pubmed ID
Authors

Ryan D. Morin, Michael D. O’Connor, Malachi Griffith, Florian Kuchenbauer, Allen Delaney, Anna-Liisa Prabhu, Yongjun Zhao, Helen McDonald, Thomas Zeng, Martin Hirst, Connie J. Eaves, Marco A. Marra

Abstract

MicroRNAs (miRNAs) are emerging as important, albeit poorly characterized, regulators of biological processes. Key to further elucidation of their roles is the generation of more complete lists of their numbers and expression changes in different cell states. Here, we report a new method for surveying the expression of small RNAs, including microRNAs, using Illumina sequencing technology. We also present a set of methods for annotating sequences deriving from known miRNAs, identifying variability in mature miRNA sequences, and identifying sequences belonging to previously unidentified miRNA genes. Application of this approach to RNA from human embryonic stem cells obtained before and after their differentiation into embryoid bodies revealed the sequences and expression levels of 334 known plus 104 novel miRNA genes. One hundred seventy-one known and 23 novel microRNA sequences exhibited significant expression differences between these two developmental states. Owing to the increased number of sequence reads, these libraries represent the deepest miRNA sampling to date, spanning nearly six orders of magnitude of expression. The predicted targets of those miRNAs enriched in either sample shared common features. Included among the high-ranked predicted gene targets are those implicated in differentiation, cell cycle control, programmed cell death, and transcriptional regulation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 768 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 24 3%
United Kingdom 9 1%
Germany 7 <1%
France 6 <1%
China 5 <1%
Brazil 5 <1%
Belgium 3 <1%
Netherlands 3 <1%
Uruguay 2 <1%
Other 18 2%
Unknown 686 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 230 30%
Student > Ph. D. Student 200 26%
Student > Master 58 8%
Professor > Associate Professor 55 7%
Student > Bachelor 52 7%
Other 113 15%
Unknown 60 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 436 57%
Biochemistry, Genetics and Molecular Biology 123 16%
Medicine and Dentistry 44 6%
Computer Science 27 4%
Neuroscience 10 1%
Other 43 6%
Unknown 85 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 17 November 2023.
All research outputs
#1,645,745
of 26,017,215 outputs
Outputs from Genome Research
#743
of 4,477 outputs
Outputs of similar age
#4,112
of 99,916 outputs
Outputs of similar age from Genome Research
#4
of 42 outputs
Altmetric has tracked 26,017,215 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 4,477 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.5. This one has done well, scoring higher than 83% 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 99,916 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 95% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.