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Mendeley readers
Attention Score in Context
| Title |
Building Markov state models with solvent dynamics
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-s2-s8 |
| Pubmed ID | |
| Authors |
Chen Gu, Huang-Wei Chang, Lutz Maibaum, Vijay S Pande, Gunnar E Carlsson, Leonidas J Guibas |
| Abstract |
Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 6% |
| Italy | 1 | 2% |
| Unknown | 58 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 37% |
| Researcher | 11 | 17% |
| Student > Postgraduate | 6 | 10% |
| Student > Bachelor | 4 | 6% |
| Professor | 4 | 6% |
| Other | 10 | 16% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 19 | 30% |
| Agricultural and Biological Sciences | 16 | 25% |
| Physics and Astronomy | 9 | 14% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Computer Science | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 5 | 8% |
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 24 February 2015.
All research outputs
#15,325,572
of 22,793,427 outputs
Outputs from BMC Bioinformatics
#5,372
of 7,280 outputs
Outputs of similar age
#180,363
of 279,642 outputs
Outputs of similar age from BMC Bioinformatics
#103
of 146 outputs
Altmetric has tracked 22,793,427 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 279,642 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.