| Title |
An improved method to detect correct protein folds using partial clustering
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-11 |
| Pubmed ID | |
| Authors |
Jianjun Zhou, David S Wishart |
| Abstract |
Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient "partial" clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. |
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% |
| Norway | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 7% |
| Czechia | 1 | 3% |
| Unknown | 27 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 33% |
| Researcher | 8 | 27% |
| Student > Bachelor | 3 | 10% |
| Student > Postgraduate | 2 | 7% |
| Student > Master | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 3 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 27% |
| Computer Science | 7 | 23% |
| Biochemistry, Genetics and Molecular Biology | 6 | 20% |
| Chemistry | 2 | 7% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 5 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 07 March 2013.
All research outputs
#14,742,867
of 22,693,205 outputs
Outputs from BMC Bioinformatics
#5,034
of 7,254 outputs
Outputs of similar age
#177,833
of 284,977 outputs
Outputs of similar age from BMC Bioinformatics
#89
of 139 outputs
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