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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, April 2008
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

2 Wikipedia pages

Readers on

312 Mendeley
21 CiteULike
8 Connotea
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Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells
Published in
Genome Research, April 2008
DOI 10.1101/gr.7179508
Pubmed ID

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, Morin RD, O'Connor MD, Griffith M, Kuchenbauer F, Delaney A, Prabhu AL, Zhao Y, McDonald H, Zeng T, Hirst M, Eaves CJ, Marra MA, R. D. Morin, M. D. O'Connor, M. Griffith, F. Kuchenbauer, A. Delaney, A.-L. Prabhu, Y. Zhao, H. McDonald, T. Zeng, M. Hirst, C. J. Eaves, M. A. Marra


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.

Mendeley readers

The data shown below were compiled from readership statistics for 312 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 17 5%
United Kingdom 7 2%
China 4 1%
Germany 3 <1%
France 3 <1%
Brazil 3 <1%
Netherlands 3 <1%
Mexico 2 <1%
Belgium 2 <1%
Other 10 3%
Unknown 258 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 113 36%
Student > Ph. D. Student 95 30%
Professor > Associate Professor 22 7%
Student > Master 18 6%
Student > Bachelor 15 5%
Other 49 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 244 78%
Biochemistry, Genetics and Molecular Biology 24 8%
Medicine and Dentistry 15 5%
Computer Science 8 3%
Unspecified 6 2%
Other 15 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 March 2012.
All research outputs
of 3,628,824 outputs
Outputs from Genome Research
of 1,801 outputs
Outputs of similar age
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Outputs of similar age from Genome Research
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Altmetric has tracked 3,628,824 research outputs across all sources so far. This one has received more attention than most of these and is in the 63rd percentile.
So far Altmetric has tracked 1,801 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 97,569 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 72% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.