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X Demographics
Mendeley readers
Attention Score in Context
| Title |
C2Maps: a network pharmacology database with comprehensive disease-gene-drug connectivity relationships
|
|---|---|
| Published in |
BMC Genomics, October 2012
|
| DOI | 10.1186/1471-2164-13-s6-s17 |
| Pubmed ID | |
| Authors |
Hui Huang, Xiaogang Wu, Ragini Pandey, Jiao Li, Guoling Zhao, Sara Ibrahim, Jake Y Chen |
| Abstract |
Network pharmacology has emerged as a new topic of study in recent years. It aims to study the myriad relationships among proteins, drugs, and disease phenotypes. The concept of molecular connectivity maps has been proposed to establish comprehensive knowledge links between molecules of interest in a given biological context. Molecular connectivity maps between drugs and genes/proteins in specific disease contexts can be particularly valuable, since the functional approach with these maps helps researchers gain global perspectives on both the therapeutic profiles and toxicological profiles of candidate drugs. |
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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | 1% |
| India | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 69 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 19% |
| Student > Ph. D. Student | 12 | 17% |
| Student > Master | 12 | 17% |
| Student > Bachelor | 9 | 13% |
| Professor | 4 | 6% |
| Other | 11 | 15% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 17% |
| Biochemistry, Genetics and Molecular Biology | 10 | 14% |
| Computer Science | 9 | 13% |
| Medicine and Dentistry | 9 | 13% |
| Psychology | 6 | 8% |
| Other | 14 | 19% |
| Unknown | 12 | 17% |
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 28 November 2012.
All research outputs
#18,321,703
of 22,687,320 outputs
Outputs from BMC Genomics
#8,146
of 10,616 outputs
Outputs of similar age
#139,950
of 183,249 outputs
Outputs of similar age from BMC Genomics
#104
of 134 outputs
Altmetric has tracked 22,687,320 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 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 183,249 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.