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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Small non-coding RNAs, mammalian cells, and viruses: regulatory interactions?
|
|---|---|
| Published in |
Retrovirology, October 2007
|
| DOI | 10.1186/1742-4690-4-74 |
| Pubmed ID | |
| Authors |
Man Lung Yeung, Monsef Benkirane, Kuan-Teh Jeang |
| Abstract |
Recent findings suggest that mammalian cells can use small non-coding RNAs (ncRNA) to regulate physiological viral infections. Here, we comment on several lines of evidence that support this concept. We discuss how viruses may in turn protect, suppress, evade, modulate, or adapt to the host cell's ncRNA regulatory schema. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Chile | 1 | 2% |
| Canada | 1 | 2% |
| Japan | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 46 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 31% |
| Student > Ph. D. Student | 12 | 24% |
| Student > Master | 6 | 12% |
| Student > Doctoral Student | 4 | 8% |
| Student > Bachelor | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 69% |
| Medicine and Dentistry | 6 | 12% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Computer Science | 1 | 2% |
| Unknown | 5 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 11 December 2015.
All research outputs
#15,351,847
of 22,835,198 outputs
Outputs from Retrovirology
#781
of 1,107 outputs
Outputs of similar age
#61,956
of 72,521 outputs
Outputs of similar age from Retrovirology
#4
of 4 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,107 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one is in the 17th percentile – i.e., 17% 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 72,521 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.