↓ Skip to main content

An efficient rRNA removal method for RNA sequencing in GC-rich bacteria

Overview of attention for article published in Microbial Informatics and Experimentation, January 2013
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 (87th percentile)

Mentioned by

twitter
5 tweeters
patent
2 patents

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
157 Mendeley
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
An efficient rRNA removal method for RNA sequencing in GC-rich bacteria
Published in
Microbial Informatics and Experimentation, January 2013
DOI 10.1186/2042-5783-3-1
Pubmed ID
Authors

Clelia Peano, Alessandro Pietrelli, Clarissa Consolandi, Elio Rossi, Luca Petiti, Letizia Tagliabue, Gianluca De Bellis, Paolo Landini

Twitter Demographics

The data shown below were collected from the profiles of 5 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 1%
Italy 2 1%
Mexico 1 <1%
Canada 1 <1%
New Zealand 1 <1%
Sweden 1 <1%
Argentina 1 <1%
France 1 <1%
Spain 1 <1%
Other 2 1%
Unknown 144 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 32%
Researcher 38 24%
Student > Master 25 16%
Student > Postgraduate 11 7%
Student > Bachelor 7 4%
Other 20 13%
Unknown 6 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 93 59%
Biochemistry, Genetics and Molecular Biology 21 13%
Immunology and Microbiology 7 4%
Environmental Science 6 4%
Computer Science 4 3%
Other 16 10%
Unknown 10 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 03 October 2019.
All research outputs
#1,945,294
of 14,904,292 outputs
Outputs from Microbial Informatics and Experimentation
#6
of 15 outputs
Outputs of similar age
#33,189
of 257,538 outputs
Outputs of similar age from Microbial Informatics and Experimentation
#2
of 3 outputs
Altmetric has tracked 14,904,292 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one scored the same or higher as 9 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 257,538 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 87% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.