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X Demographics
Mendeley readers
Attention Score in Context
| Title |
K-Map: connecting kinases with therapeutics for drug repurposing and development
|
|---|---|
| Published in |
Human Genomics, September 2013
|
| DOI | 10.1186/1479-7364-7-20 |
| Pubmed ID | |
| Authors |
Jihye Kim, Minjae Yoo, Jaewoo Kang, Aik Choon Tan |
| Abstract |
Protein kinases play important roles in regulating signal transduction in eukaryotic cells. Due to evolutionary conserved binding sites in the catalytic domain of the kinases, most inhibitors that target these sites promiscuously inhibit multiple kinases. Quantitative analysis can reveal complex and unexpected interactions between protein kinases and kinase inhibitors, providing opportunities for identifying multi-targeted inhibitors of specific diverse kinases for drug repurposing and development. We have developed K-Map-a novel and user-friendly web-based program that systematically connects a set of query kinases to kinase inhibitors based on quantitative profiles of the kinase inhibitor activities. Users can use K-Map to find kinase inhibitors for a set of query kinases (obtained from high-throughput 'omics' experiments) or to reveal new interactions between kinases and kinase inhibitors for rational drug combination studies. |
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 Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 42 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 23% |
| Researcher | 9 | 21% |
| Student > Master | 3 | 7% |
| Student > Bachelor | 2 | 5% |
| Professor | 2 | 5% |
| Other | 7 | 16% |
| Unknown | 10 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 23% |
| Agricultural and Biological Sciences | 7 | 16% |
| Medicine and Dentistry | 5 | 12% |
| Computer Science | 3 | 7% |
| Engineering | 3 | 7% |
| Other | 6 | 14% |
| Unknown | 9 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 23 September 2013.
All research outputs
#4,657,320
of 25,373,627 outputs
Outputs from Human Genomics
#112
of 564 outputs
Outputs of similar age
#39,163
of 214,768 outputs
Outputs of similar age from Human Genomics
#2
of 4 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 80% 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 214,768 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 81% of its contemporaries.
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. This one has scored higher than 2 of them.