| Title |
Constructing patch-based ligand-binding pocket database for predicting function of proteins
|
|---|---|
| Published in |
BMC Bioinformatics, March 2012
|
| DOI | 10.1186/1471-2105-13-s2-s7 |
| Pubmed ID | |
| Authors |
Lee Sael, Daisuke Kihara |
| Abstract |
Many of solved tertiary structures of unknown functions do not have global sequence and structural similarities to proteins of known function. Often functional clues of unknown proteins can be obtained by predicting small ligand molecules that bind to the proteins. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 11% |
| Korea, Republic of | 1 | 6% |
| Unknown | 15 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 28% |
| Researcher | 4 | 22% |
| Professor | 2 | 11% |
| Student > Master | 2 | 11% |
| Professor > Associate Professor | 2 | 11% |
| Other | 2 | 11% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 61% |
| Engineering | 2 | 11% |
| Computer Science | 2 | 11% |
| Mathematics | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 1 | 6% |
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 14 March 2012.
All research outputs
#15,692,595
of 23,318,744 outputs
Outputs from BMC Bioinformatics
#5,483
of 7,384 outputs
Outputs of similar age
#101,628
of 157,929 outputs
Outputs of similar age from BMC Bioinformatics
#48
of 62 outputs
Altmetric has tracked 23,318,744 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 7,384 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 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 157,929 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.