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Mendeley readers
Attention Score in Context
| Title |
NOXclass: prediction of protein-protein interaction types
|
|---|---|
| Published in |
BMC Bioinformatics, January 2006
|
| DOI | 10.1186/1471-2105-7-27 |
| Pubmed ID | |
| Authors |
Hongbo Zhu, Francisco S Domingues, Ingolf Sommer, Thomas Lengauer |
| Abstract |
Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 81 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 7% |
| Student > Ph. D. Student | 3 | 4% |
| Student > Doctoral Student | 2 | 2% |
| Student > Bachelor | 1 | 1% |
| Professor | 1 | 1% |
| Other | 4 | 5% |
| Unknown | 66 | 80% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 7% |
| Biochemistry, Genetics and Molecular Biology | 5 | 6% |
| Agricultural and Biological Sciences | 2 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Medicine and Dentistry | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 66 | 80% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 20 June 2011.
All research outputs
#14,600,874
of 25,374,917 outputs
Outputs from BMC Bioinformatics
#4,029
of 7,692 outputs
Outputs of similar age
#146,984
of 173,545 outputs
Outputs of similar age from BMC Bioinformatics
#40
of 46 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,692 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 173,545 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.