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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mining the entire Protein DataBank for frequent spatially cohesive amino acid patterns
|
|---|---|
| Published in |
BioData Mining, January 2015
|
| DOI | 10.1186/s13040-015-0038-4 |
| Pubmed ID | |
| Authors |
Pieter Meysman, Cheng Zhou, Boris Cule, Bart Goethals, Kris Laukens |
| Abstract |
The three-dimensional structure of a protein is an essential aspect of its functionality. Despite the large diversity in protein structures and functionality, it is known that there are common patterns and preferences in the contacts between amino acid residues, or between residues and other biomolecules, such as DNA. The discovery and characterization of these patterns is an important research topic within structural biology as it can give fundamental insight into protein structures and can aid in the prediction of unknown structures. |
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 % |
|---|---|---|
| Belgium | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 34 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 28% |
| Researcher | 7 | 19% |
| Student > Doctoral Student | 4 | 11% |
| Student > Master | 4 | 11% |
| Student > Bachelor | 3 | 8% |
| Other | 4 | 11% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 33% |
| Biochemistry, Genetics and Molecular Biology | 8 | 22% |
| Agricultural and Biological Sciences | 8 | 22% |
| Chemical Engineering | 2 | 6% |
| Chemistry | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 3 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 15 December 2015.
All research outputs
#13,426,623
of 22,789,566 outputs
Outputs from BioData Mining
#186
of 307 outputs
Outputs of similar age
#174,085
of 353,101 outputs
Outputs of similar age from BioData Mining
#7
of 11 outputs
Altmetric has tracked 22,789,566 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 37th percentile – i.e., 37% 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 353,101 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.