You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Attention Score in Context
| Title |
Discovery and characterization of medaka miRNA genes by next generation sequencing platform
|
|---|---|
| Published in |
BMC Genomics, December 2010
|
| DOI | 10.1186/1471-2164-11-s4-s8 |
| Pubmed ID | |
| Authors |
Sung-Chou Li, Wen-Ching Chan, Meng-Ru Ho, Kuo-Wang Tsai, Ling-Yueh Hu, Chun-Hung Lai, Chun-Nan Hsu, Pung-Pung Hwang, Wen-chang Lin |
| Abstract |
MicroRNAs (miRNAs) are endogenous non-protein-coding RNA genes which exist in a wide variety of organisms, including animals, plants, virus and even unicellular organisms. Medaka (Oryzias latipes) is a useful model organism among vertebrate animals. However, no medaka miRNAs have been investigated systematically. It is beneficial to conduct a genome-wide miRNA discovery study using the next generation sequencing (NGS) technology, which has emerged as a powerful sequencing tool for high-throughput analysis. |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hong Kong | 1 | 1% |
| Brazil | 1 | 1% |
| United Kingdom | 1 | 1% |
| China | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 73 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 27% |
| Student > Ph. D. Student | 20 | 26% |
| Student > Master | 9 | 12% |
| Student > Bachelor | 6 | 8% |
| Lecturer | 6 | 8% |
| Other | 11 | 14% |
| Unknown | 5 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 49 | 63% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Computer Science | 3 | 4% |
| Social Sciences | 2 | 3% |
| Medicine and Dentistry | 2 | 3% |
| Other | 3 | 4% |
| Unknown | 8 | 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 12 November 2014.
All research outputs
#7,453,827
of 22,787,797 outputs
Outputs from BMC Genomics
#3,597
of 10,647 outputs
Outputs of similar age
#54,090
of 180,425 outputs
Outputs of similar age from BMC Genomics
#30
of 83 outputs
Altmetric has tracked 22,787,797 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 10,647 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 180,425 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.