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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
The Collaborative Drug Discovery (CDD) Database
|
|---|---|
| Chapter number | 10 |
| Book title |
In Silico Models for Drug Discovery
|
| Published in |
Methods in molecular biology, March 2013
|
| DOI | 10.1007/978-1-62703-342-8_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-341-1, 978-1-62703-342-8
|
| Authors |
Ekins S, Bunin BA, Sean Ekins, Barry A. Bunin |
| Editors |
Sandhya Kortagere |
| Abstract |
The broad goals of Collaborative Drug Discovery (CDD) are to enable a collaborative "cloud-based" tool to be used to bring together neglected disease researchers and other researchers from usually separate areas, to collaborate and to share compounds and drug discovery data in the research community, which will ultimately result in long-term improvements in the research enterprise and health care delivery. This chapter briefly introduces CDD software and describes applications in antimalarial and tuberculosis research. |
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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 6% |
| United States | 1 | 3% |
| Italy | 1 | 3% |
| Portugal | 1 | 3% |
| Unknown | 30 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 23% |
| Researcher | 6 | 17% |
| Student > Master | 4 | 11% |
| Other | 3 | 9% |
| Student > Bachelor | 3 | 9% |
| Other | 6 | 17% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 17% |
| Chemistry | 5 | 14% |
| Computer Science | 4 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Other | 6 | 17% |
| Unknown | 3 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 17 February 2016.
All research outputs
#3,562,952
of 22,774,233 outputs
Outputs from Methods in molecular biology
#861
of 13,091 outputs
Outputs of similar age
#29,991
of 194,835 outputs
Outputs of similar age from Methods in molecular biology
#4
of 35 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,091 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 93% 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 194,835 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 84% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.