↓ Skip to main content

Strand-specific libraries for high throughput RNA sequencing (RNA-Seq) prepared without poly(A) selection

Overview of attention for article published in Silence, December 2012
Altmetric Badge

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)

Mentioned by

blogs
2 blogs
twitter
18 X users
patent
2 patents

Citations

dimensions_citation
122 Dimensions

Readers on

mendeley
216 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Strand-specific libraries for high throughput RNA sequencing (RNA-Seq) prepared without poly(A) selection
Published in
Silence, December 2012
DOI 10.1186/1758-907x-3-9
Pubmed ID
Authors

Zhao Zhang, William E Theurkauf, Zhiping Weng, Phillip D Zamore

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 216 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 2 <1%
Portugal 1 <1%
Sweden 1 <1%
Brazil 1 <1%
Germany 1 <1%
Mexico 1 <1%
Taiwan 1 <1%
Denmark 1 <1%
Other 1 <1%
Unknown 202 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 55 25%
Researcher 54 25%
Student > Master 18 8%
Student > Doctoral Student 14 6%
Student > Bachelor 12 6%
Other 39 18%
Unknown 24 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 108 50%
Biochemistry, Genetics and Molecular Biology 48 22%
Medicine and Dentistry 10 5%
Engineering 7 3%
Computer Science 3 1%
Other 9 4%
Unknown 31 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 11 May 2023.
All research outputs
#1,409,012
of 25,877,363 outputs
Outputs from Silence
#2
of 28 outputs
Outputs of similar age
#11,793
of 291,022 outputs
Outputs of similar age from Silence
#1
of 1 outputs
Altmetric has tracked 25,877,363 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one scored the same or higher as 26 of them.
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 291,022 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 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