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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Reducing ligation bias of small RNAs in libraries for next generation sequencing
|
|---|---|
| Published in |
Silence, May 2012
|
| DOI | 10.1186/1758-907x-3-4 |
| Pubmed ID | |
| Authors |
Karim Sorefan, Helio Pais, Adam E Hall, Ana Kozomara, Sam Griffiths-Jones, Vincent Moulton, Tamas Dalmay |
| Abstract |
The use of nucleic acid-modifying enzymes has driven the rapid advancement in molecular biology. Understanding their function is important for modifying or improving their activity. However, functional analysis usually relies upon low-throughput experiments. Here we present a method for functional analysis of nucleic acid-modifying enzymes using next generation sequencing. |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 6 | 40% |
| United States | 2 | 13% |
| Hong Kong | 1 | 7% |
| Spain | 1 | 7% |
| France | 1 | 7% |
| Unknown | 4 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 53% |
| Scientists | 6 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 2% |
| South Africa | 2 | 1% |
| France | 1 | <1% |
| Norway | 1 | <1% |
| Italy | 1 | <1% |
| Germany | 1 | <1% |
| Turkey | 1 | <1% |
| Brazil | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 183 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 63 | 32% |
| Student > Ph. D. Student | 50 | 25% |
| Student > Bachelor | 16 | 8% |
| Student > Master | 14 | 7% |
| Professor > Associate Professor | 11 | 6% |
| Other | 24 | 12% |
| Unknown | 19 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 98 | 50% |
| Biochemistry, Genetics and Molecular Biology | 57 | 29% |
| Computer Science | 7 | 4% |
| Engineering | 5 | 3% |
| Medicine and Dentistry | 4 | 2% |
| Other | 3 | 2% |
| Unknown | 23 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 12 May 2015.
All research outputs
#1,587,470
of 22,665,794 outputs
Outputs from Silence
#4
of 28 outputs
Outputs of similar age
#10,135
of 165,091 outputs
Outputs of similar age from Silence
#1
of 3 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd 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 7.9. This one scored the same or higher as 24 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 165,091 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 93% 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. This one has scored higher than all of them