| Title |
Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs)
|
|---|---|
| Published in |
BMC Bioinformatics, February 2013
|
| DOI | 10.1186/1471-2105-14-s3-s13 |
| Pubmed ID | |
| Authors |
Zhouxi Wang, Pengcheng Yin, Joslynn S Lee, Ramya Parasuram, Srinivas Somarowthu, Mary Jo Ondrechen |
| Abstract |
The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and to predict function from structure would add tremendous value to structural genomics data. We report on a new method, Structurally Aligned Local Sites of Activity (SALSA), for the prediction of biochemical function based on a local structural match at the predicted catalytic or binding site. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
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 % |
|---|---|---|
| France | 2 | 6% |
| Denmark | 1 | 3% |
| India | 1 | 3% |
| Unknown | 32 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 36% |
| Student > Bachelor | 6 | 17% |
| Student > Master | 5 | 14% |
| Other | 2 | 6% |
| Student > Doctoral Student | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 6 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 44% |
| Biochemistry, Genetics and Molecular Biology | 8 | 22% |
| Chemistry | 2 | 6% |
| Computer Science | 1 | 3% |
| Chemical Engineering | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 6 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 01 May 2018.
All research outputs
#5,857,742
of 22,701,287 outputs
Outputs from BMC Bioinformatics
#2,167
of 7,254 outputs
Outputs of similar age
#48,008
of 192,986 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 159 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,254 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 69% 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 192,986 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.