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Mendeley readers
Attention Score in Context
Chapter title |
Using Deep Sequencing Data for Identification of Editing Sites in Mature miRNAs
|
---|---|
Chapter number | 14 |
Book title |
RNA Bioinformatics
|
Published in |
Methods in molecular biology, December 2014
|
DOI | 10.1007/978-1-4939-2291-8_14 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2290-1, 978-1-4939-2291-8
|
Authors |
Shahar Alon, Eli Eisenberg |
Editors |
Ernesto Picardi |
Abstract |
Deep sequencing has many possible applications; one of them is the identification and quantification of RNA editing sites. The most common type of RNA editing is adenosine to inosine (A-to-I) editing. A prerequisite for this editing process is a double-stranded RNA (dsRNA) structure. Such dsRNAs are formed as part of the microRNA (miRNA) maturation process, and it is therefore expected that miRNAs are affected by A-to-I editing. Indeed, tens of editing sites were found in miRNAs, some of which change the miRNA binding specificity. Here, we describe a protocol for the identification of RNA editing sites in mature miRNAs using deep sequencing data. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 7% |
Germany | 1 | 7% |
Unknown | 12 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 36% |
Professor | 4 | 29% |
Student > Ph. D. Student | 3 | 21% |
Other | 1 | 7% |
Unknown | 1 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 8 | 57% |
Biochemistry, Genetics and Molecular Biology | 4 | 29% |
Medicine and Dentistry | 1 | 7% |
Unknown | 1 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 16 January 2015.
All research outputs
#3,729,492
of 22,778,347 outputs
Outputs from Methods in molecular biology
#934
of 13,092 outputs
Outputs of similar age
#53,164
of 354,395 outputs
Outputs of similar age from Methods in molecular biology
#53
of 969 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,092 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 92% 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 354,395 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 84% of its contemporaries.
We're also able to compare this research output to 969 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 94% of its contemporaries.