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X Demographics
Mendeley readers
Attention Score in Context
Title |
ROKU: a novel method for identification of tissue-specific genes
|
---|---|
Published in |
BMC Bioinformatics, June 2006
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DOI | 10.1186/1471-2105-7-294 |
Pubmed ID | |
Authors |
Koji Kadota, Jiazhen Ye, Yuji Nakai, Tohru Terada, Kentaro Shimizu |
Abstract |
One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. |
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 % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 3% |
Japan | 2 | 2% |
France | 1 | <1% |
United Kingdom | 1 | <1% |
Canada | 1 | <1% |
Germany | 1 | <1% |
Russia | 1 | <1% |
Malaysia | 1 | <1% |
Belgium | 1 | <1% |
Other | 1 | <1% |
Unknown | 102 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 27 | 23% |
Researcher | 26 | 22% |
Professor > Associate Professor | 11 | 9% |
Student > Master | 11 | 9% |
Student > Postgraduate | 7 | 6% |
Other | 14 | 12% |
Unknown | 20 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 47 | 41% |
Biochemistry, Genetics and Molecular Biology | 29 | 25% |
Medicine and Dentistry | 7 | 6% |
Computer Science | 6 | 5% |
Mathematics | 2 | 2% |
Other | 6 | 5% |
Unknown | 19 | 16% |
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 29 November 2017.
All research outputs
#12,853,669
of 22,664,267 outputs
Outputs from BMC Bioinformatics
#3,776
of 7,247 outputs
Outputs of similar age
#54,309
of 64,131 outputs
Outputs of similar age from BMC Bioinformatics
#33
of 43 outputs
Altmetric has tracked 22,664,267 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 45th percentile – i.e., 45% 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 64,131 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.