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X Demographics
Mendeley readers
Attention Score in Context
Title |
On the validity versus utility of activity landscapes: are all activity cliffs statistically significant?
|
---|---|
Published in |
Journal of Cheminformatics, April 2014
|
DOI | 10.1186/1758-2946-6-11 |
Pubmed ID | |
Authors |
Rajarshi Guha, José L Medina-Franco |
Abstract |
Most work on the topic of activity landscapes has focused on their quantitative description and visual representation, with the aim of aiding navigation of SAR. Recent developments have addressed applications such as quantifying the proportion of activity cliffs, investigating the predictive abilities of activity landscape methods and so on. However, all these publications have worked under the assumption that the activity landscape models are "real" (i.e., statistically significant). |
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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 1 | 4% |
Bulgaria | 1 | 4% |
Germany | 1 | 4% |
Romania | 1 | 4% |
Unknown | 21 | 84% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 28% |
Student > Ph. D. Student | 5 | 20% |
Professor > Associate Professor | 3 | 12% |
Student > Doctoral Student | 3 | 12% |
Other | 1 | 4% |
Other | 2 | 8% |
Unknown | 4 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 8 | 32% |
Computer Science | 6 | 24% |
Agricultural and Biological Sciences | 2 | 8% |
Medicine and Dentistry | 2 | 8% |
Biochemistry, Genetics and Molecular Biology | 1 | 4% |
Other | 1 | 4% |
Unknown | 5 | 20% |
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 02 April 2014.
All research outputs
#18,369,403
of 22,751,628 outputs
Outputs from Journal of Cheminformatics
#794
of 828 outputs
Outputs of similar age
#163,251
of 225,531 outputs
Outputs of similar age from Journal of Cheminformatics
#21
of 23 outputs
Altmetric has tracked 22,751,628 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 828 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 1st percentile – i.e., 1% 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 225,531 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.