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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The good, the bad and the dubious: VHELIBS, a validation helper for ligands and binding sites
|
|---|---|
| Published in |
Journal of Cheminformatics, July 2013
|
| DOI | 10.1186/1758-2946-5-36 |
| Pubmed ID | |
| Authors |
Adrià Cereto-Massagué, María José Ojeda, Robbie P Joosten, Cristina Valls, Miquel Mulero, M Josepa Salvado, Anna Arola-Arnal, Lluís Arola, Santiago Garcia-Vallvé, Gerard Pujadas |
| Abstract |
Many Protein Data Bank (PDB) users assume that the deposited structural models are of high quality but forget that these models are derived from the interpretation of experimental data. The accuracy of atom coordinates is not homogeneous between models or throughout the same model. To avoid basing a research project on a flawed model, we present a tool for assessing the quality of ligands and binding sites in crystallographic models from the PDB. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 50% |
| Germany | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 4% |
| Brazil | 2 | 3% |
| India | 1 | 1% |
| Unknown | 67 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 22% |
| Researcher | 16 | 22% |
| Student > Master | 9 | 12% |
| Student > Bachelor | 7 | 10% |
| Professor > Associate Professor | 7 | 10% |
| Other | 13 | 18% |
| Unknown | 5 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 19 | 26% |
| Biochemistry, Genetics and Molecular Biology | 16 | 22% |
| Agricultural and Biological Sciences | 16 | 22% |
| Computer Science | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 9 | 12% |
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 12 August 2013.
All research outputs
#4,038,804
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#387
of 891 outputs
Outputs of similar age
#33,560
of 202,567 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 9 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has gotten more attention than average, scoring higher than 56% 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 202,567 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 83% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.