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Mendeley readers
Attention Score in Context
| Title |
Data-driven normalization strategies for high-throughput quantitative RT-PCR
|
|---|---|
| Published in |
BMC Bioinformatics, April 2009
|
| DOI | 10.1186/1471-2105-10-110 |
| Pubmed ID | |
| Authors |
Jessica C Mar, Yasumasa Kimura, Kate Schroder, Katharine M Irvine, Yoshihide Hayashizaki, Harukazu Suzuki, David Hume, John Quackenbush |
Mendeley readers
The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 4% |
| Australia | 2 | 1% |
| Norway | 2 | 1% |
| Germany | 2 | 1% |
| Brazil | 2 | 1% |
| Mexico | 2 | 1% |
| Sweden | 2 | 1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 5 | 3% |
| Unknown | 139 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 47 | 28% |
| Researcher | 46 | 28% |
| Student > Master | 18 | 11% |
| Professor > Associate Professor | 13 | 8% |
| Professor | 7 | 4% |
| Other | 21 | 13% |
| Unknown | 13 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 83 | 50% |
| Biochemistry, Genetics and Molecular Biology | 21 | 13% |
| Medicine and Dentistry | 15 | 9% |
| Computer Science | 10 | 6% |
| Mathematics | 7 | 4% |
| Other | 13 | 8% |
| Unknown | 16 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 25 July 2013.
All research outputs
#8,759,452
of 25,837,817 outputs
Outputs from BMC Bioinformatics
#3,313
of 7,763 outputs
Outputs of similar age
#38,787
of 108,870 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 37 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 49th percentile – i.e., 49% 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 108,870 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.