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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of kinase inhibitor response using activity profiling, in vitro screening, and elastic net regression
|
|---|---|
| Published in |
BMC Systems Biology, June 2014
|
| DOI | 10.1186/1752-0509-8-74 |
| Pubmed ID | |
| Authors |
Trish P Tran, Edison Ong, Andrew P Hodges, Giovanni Paternostro, Carlo Piermarocchi |
| Abstract |
Many kinase inhibitors have been approved as cancer therapies. Recently, libraries of kinase inhibitors have been extensively profiled, thus providing a map of the strength of action of each compound on a large number of its targets. These profiled libraries define drug-kinase networks that can predict the effectiveness of untested drugs and elucidate the roles of specific kinases in different cellular systems. Predictions of drug effectiveness based on a comprehensive network model of cellular signalling are difficult, due to our partial knowledge of the complex biological processes downstream of the targeted kinases. |
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 % |
|---|---|---|
| United States | 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 40 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 26% |
| Student > Ph. D. Student | 9 | 21% |
| Student > Master | 5 | 12% |
| Student > Bachelor | 3 | 7% |
| Professor > Associate Professor | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 8 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 19% |
| Biochemistry, Genetics and Molecular Biology | 7 | 17% |
| Agricultural and Biological Sciences | 6 | 14% |
| Chemistry | 5 | 12% |
| Psychology | 2 | 5% |
| Other | 6 | 14% |
| Unknown | 8 | 19% |
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 21 July 2014.
All research outputs
#18,375,064
of 22,758,963 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#163,781
of 227,907 outputs
Outputs of similar age from BMC Systems Biology
#21
of 27 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% 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 227,907 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 27 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.