| Title |
The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation
|
|---|---|
| Published in |
Genome Biology, January 2008
|
| DOI | 10.1186/gb-2008-9-1-r8 |
| Pubmed ID | |
| Authors |
Shirley Wu, Mike P Liang, Russ B Altman |
| Abstract |
Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low. |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 11% |
| United Kingdom | 1 | 3% |
| Unknown | 33 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 37% |
| Researcher | 6 | 16% |
| Student > Master | 5 | 13% |
| Student > Bachelor | 4 | 11% |
| Professor | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 37% |
| Agricultural and Biological Sciences | 11 | 29% |
| Engineering | 3 | 8% |
| Chemistry | 3 | 8% |
| Mathematics | 2 | 5% |
| Other | 4 | 11% |
| Unknown | 1 | 3% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 January 2009.
All research outputs
#6,296,284
of 25,373,627 outputs
Outputs from Genome Biology
#3,028
of 4,467 outputs
Outputs of similar age
#33,545
of 166,883 outputs
Outputs of similar age from Genome Biology
#14
of 34 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 32nd percentile – i.e., 32% 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 166,883 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 34 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 58% of its contemporaries.