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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A new approach for prediction of tumor sensitivity to targeted drugs based on functional data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-239 |
| Pubmed ID | |
| Authors |
Noah Berlow, Lara E Davis, Emma L Cantor, Bernard Séguin, Charles Keller, Ranadip Pal |
X Demographics
The data shown below were collected from the profiles of 14 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 | 4 | 29% |
| Ireland | 1 | 7% |
| Singapore | 1 | 7% |
| Germany | 1 | 7% |
| Unknown | 7 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 6 | 43% |
| Members of the public | 4 | 29% |
| Scientists | 3 | 21% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 5% |
| Netherlands | 1 | 2% |
| India | 1 | 2% |
| Brazil | 1 | 2% |
| China | 1 | 2% |
| Belgium | 1 | 2% |
| Unknown | 53 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 33% |
| Researcher | 13 | 21% |
| Student > Bachelor | 5 | 8% |
| Other | 5 | 8% |
| Professor > Associate Professor | 5 | 8% |
| Other | 11 | 18% |
| Unknown | 2 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 28% |
| Computer Science | 10 | 16% |
| Biochemistry, Genetics and Molecular Biology | 9 | 15% |
| Medicine and Dentistry | 6 | 10% |
| Engineering | 5 | 8% |
| Other | 10 | 16% |
| Unknown | 4 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 30 July 2014.
All research outputs
#3,153,140
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#951
of 7,793 outputs
Outputs of similar age
#25,920
of 214,075 outputs
Outputs of similar age from BMC Bioinformatics
#20
of 81 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 87% 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 214,075 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.