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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sensitive Detection of Viral Transcripts in Human Tumor Transcriptomes
|
|---|---|
| Published in |
PLoS Computational Biology, October 2013
|
| DOI | 10.1371/journal.pcbi.1003228 |
| Pubmed ID | |
| Authors |
Sven-Eric Schelhorn, Matthias Fischer, Laura Tolosi, Janine Altmüller, Peter Nürnberg, Herbert Pfister, Thomas Lengauer, Frank Berthold |
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 % |
|---|---|---|
| United States | 1 | 33% |
| Germany | 1 | 33% |
| India | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| United Kingdom | 1 | 1% |
| Unknown | 72 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 29% |
| Student > Ph. D. Student | 21 | 28% |
| Student > Master | 8 | 11% |
| Student > Postgraduate | 5 | 7% |
| Professor | 4 | 5% |
| Other | 10 | 13% |
| Unknown | 6 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 28 | 37% |
| Biochemistry, Genetics and Molecular Biology | 11 | 14% |
| Computer Science | 9 | 12% |
| Medicine and Dentistry | 8 | 11% |
| Immunology and Microbiology | 3 | 4% |
| Other | 7 | 9% |
| Unknown | 10 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 October 2013.
All research outputs
#16,681,672
of 26,017,215 outputs
Outputs from PLoS Computational Biology
#7,065
of 9,038 outputs
Outputs of similar age
#132,763
of 224,557 outputs
Outputs of similar age from PLoS Computational Biology
#96
of 135 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,038 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 19th percentile – i.e., 19% 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 224,557 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.