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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Web-Based Computational Chemistry Education with CHARMMing I: Lessons and Tutorial
|
|---|---|
| Published in |
PLoS Computational Biology, July 2014
|
| DOI | 10.1371/journal.pcbi.1003719 |
| Pubmed ID | |
| Authors |
Benjamin T. Miller, Rishi P. Singh, Vinushka Schalk, Yuri Pevzner, Jingjun Sun, Carrie S. Miller, Stefan Boresch, Toshiko Ichiye, Bernard R. Brooks, H. Lee Woodcock |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 17% |
| United States | 2 | 17% |
| India | 1 | 8% |
| Japan | 1 | 8% |
| Italy | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 50% |
| Members of the public | 5 | 42% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 2% |
| Chile | 1 | 1% |
| Hungary | 1 | 1% |
| Czechia | 1 | 1% |
| United Kingdom | 1 | 1% |
| Ukraine | 1 | 1% |
| Canada | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 76 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 20% |
| Researcher | 16 | 19% |
| Professor > Associate Professor | 8 | 9% |
| Professor | 8 | 9% |
| Student > Bachelor | 8 | 9% |
| Other | 19 | 22% |
| Unknown | 9 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 26 | 31% |
| Agricultural and Biological Sciences | 14 | 16% |
| Biochemistry, Genetics and Molecular Biology | 9 | 11% |
| Engineering | 6 | 7% |
| Physics and Astronomy | 4 | 5% |
| Other | 17 | 20% |
| Unknown | 9 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 01 September 2021.
All research outputs
#1,405,885
of 25,837,817 outputs
Outputs from PLoS Computational Biology
#1,166
of 9,027 outputs
Outputs of similar age
#13,594
of 242,570 outputs
Outputs of similar age from PLoS Computational Biology
#14
of 166 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,027 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 87% 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 242,570 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.