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Mendeley readers
Attention Score in Context
| Title |
High-efficiency RNA cloning enables accurate quantification of miRNA expression by deep sequencing
|
|---|---|
| Published in |
Genome Biology, December 2013
|
| DOI | 10.1186/gb-2013-14-10-r109 |
| Pubmed ID | |
| Authors |
Zhaojie Zhang, Jerome E Lee, Kent Riemondy, Emily M Anderson, Rui Yi |
| Abstract |
Small RNA cloning and sequencing is uniquely positioned as a genome-wide approach to quantify miRNAs with single-nucleotide resolution. However, significant biases introduced by RNA ligation in current protocols lead to inaccurate miRNA quantification by 1000-fold. Here we report an RNA cloning method that achieves over 95% efficiency for both 5′ and 3′ ligations. It achieves accurate quantification of synthetic miRNAs with less than two-fold deviation from the anticipated value and over a dynamic range of four orders of magnitude. Taken together, this high-efficiency RNA cloning method permits accurate genome-wide miRNA profiling from total RNAs. |
Mendeley readers
The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| United Kingdom | 2 | 2% |
| Italy | 1 | <1% |
| Austria | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Czechia | 1 | <1% |
| India | 1 | <1% |
| South Africa | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 108 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 40 | 33% |
| Student > Ph. D. Student | 29 | 24% |
| Student > Master | 11 | 9% |
| Student > Bachelor | 10 | 8% |
| Other | 8 | 7% |
| Other | 13 | 11% |
| Unknown | 12 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 51 | 41% |
| Biochemistry, Genetics and Molecular Biology | 39 | 32% |
| Computer Science | 8 | 7% |
| Engineering | 4 | 3% |
| Neuroscience | 3 | 2% |
| Other | 6 | 5% |
| Unknown | 12 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 31 October 2023.
All research outputs
#2,427,971
of 25,374,917 outputs
Outputs from Genome Biology
#1,966
of 4,467 outputs
Outputs of similar age
#26,821
of 320,160 outputs
Outputs of similar age from Genome Biology
#43
of 97 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 55% 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 320,160 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 91% of its contemporaries.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.