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Mendeley readers
Attention Score in Context
| Title |
Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information
|
|---|---|
| Published in |
BMC Bioinformatics, June 2010
|
| DOI | 10.1186/1471-2105-11-301 |
| Pubmed ID | |
| Authors |
Jagat S Chauhan, Nitish K Mishra, Gajendra PS Raghava |
| Abstract |
Guanosine triphosphate (GTP)-binding proteins play an important role in regulation of G-protein. Thus prediction of GTP interacting residues in a protein is one of the major challenges in the field of the computational biology. In this study, an attempt has been made to develop a computational method for predicting GTP interacting residues in a protein with high accuracy (Acc), precision (Prec) and recall (Rc). |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 6% |
| Unknown | 32 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 50% |
| Researcher | 4 | 12% |
| Student > Master | 4 | 12% |
| Student > Bachelor | 2 | 6% |
| Student > Doctoral Student | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 3 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 41% |
| Biochemistry, Genetics and Molecular Biology | 8 | 24% |
| Engineering | 3 | 9% |
| Computer Science | 2 | 6% |
| Medicine and Dentistry | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 3 | 9% |
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 10 October 2010.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#34,045
of 96,101 outputs
Outputs of similar age from BMC Bioinformatics
#33
of 71 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% 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 has gotten more attention than average, scoring higher than 50% 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 96,101 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.