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Attention Score in Context
Chapter title |
Small Non-Coding RNAs: A Quick Look in the Rearview Mirror.
|
---|---|
Chapter number | 1 |
Book title |
Small Non-Coding RNAs
|
Published in |
Methods in molecular biology, January 2015
|
DOI | 10.1007/978-1-4939-2547-6_1 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2546-9, 978-1-4939-2547-6
|
Authors |
Guillaume Clerget, Yoann Abel, Mathieu Rederstorff, Clerget, Guillaume, Abel, Yoann, Rederstorff, Mathieu |
Abstract |
The revolution of miRNA discovery, in the early 2000s, shed a new light in the exciting field of small non-coding RNAs. Since then, and owing to outstanding breakthroughs in RNomic techniques, novel small non-coding RNA families have been regularly discovered, e.g., piRNAs, tiRNAs, and many others.In this review, we provide a very succinct historical and functional overview on most prominent small non-coding RNA families. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 4 | 33% |
Student > Ph. D. Student | 3 | 25% |
Researcher | 3 | 25% |
Student > Doctoral Student | 1 | 8% |
Professor > Associate Professor | 1 | 8% |
Other | 0 | 0% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 42% |
Agricultural and Biological Sciences | 2 | 17% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 17% |
Veterinary Science and Veterinary Medicine | 1 | 8% |
Immunology and Microbiology | 1 | 8% |
Other | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 22 March 2015.
All research outputs
#20,265,771
of 22,796,179 outputs
Outputs from Methods in molecular biology
#9,899
of 13,111 outputs
Outputs of similar age
#295,776
of 353,053 outputs
Outputs of similar age from Methods in molecular biology
#635
of 996 outputs
Altmetric has tracked 22,796,179 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,111 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% 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 353,053 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 996 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.