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Mendeley readers
Attention Score in Context
| Title |
miTarget: microRNA target gene prediction using a support vector machine
|
|---|---|
| Published in |
BMC Bioinformatics, September 2006
|
| DOI | 10.1186/1471-2105-7-411 |
| Pubmed ID | |
| Authors |
Sung-Kyu Kim, Jin-Wu Nam, Je-Keun Rhee, Wha-Jin Lee, Byoung-Tak Zhang |
| Abstract |
MicroRNAs (miRNAs) are small noncoding RNAs, which play significant roles as posttranscriptional regulators. The functions of animal miRNAs are generally based on complementarity for their 5' components. Although several computational miRNA target-gene prediction methods have been proposed, they still have limitations in revealing actual target genes. |
Mendeley readers
The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| Germany | 3 | 2% |
| Italy | 2 | 1% |
| Mexico | 2 | 1% |
| United Kingdom | 2 | 1% |
| Brazil | 1 | <1% |
| Canada | 1 | <1% |
| Turkey | 1 | <1% |
| Thailand | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 169 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 51 | 27% |
| Student > Ph. D. Student | 42 | 22% |
| Student > Master | 31 | 16% |
| Professor > Associate Professor | 14 | 7% |
| Professor | 8 | 4% |
| Other | 29 | 15% |
| Unknown | 16 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 76 | 40% |
| Computer Science | 43 | 23% |
| Biochemistry, Genetics and Molecular Biology | 29 | 15% |
| Engineering | 8 | 4% |
| Medicine and Dentistry | 6 | 3% |
| Other | 14 | 7% |
| Unknown | 15 | 8% |
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 22 November 2008.
All research outputs
#7,454,298
of 22,789,076 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#23,563
of 67,652 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 42 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 67,652 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 42 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.