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Mendeley readers
| Title |
MeDor: a metaserver for predicting protein disorder
|
|---|---|
| Published in |
BMC Genomics, September 2008
|
| DOI | 10.1186/1471-2164-9-s2-s25 |
| Pubmed ID | |
| Authors |
Philippe Lieutaud, Bruno Canard, Sonia Longhi |
| Abstract |
We have previously shown that using multiple prediction methods improves the accuracy of disorder predictions. It is, however, a time-consuming procedure, since individual outputs of multiple predictions have to be retrieved, compared to each other and a comprehensive view of the results can only be obtained through a manual, fastidious, non-automated procedure. We herein describe a new web metaserver, MeDor, which allows fast, simultaneous analysis of a query sequence by multiple predictors and provides a graphical interface with a unified view of the outputs. |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 2% |
| Unknown | 45 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 28% |
| Student > Ph. D. Student | 11 | 24% |
| Student > Master | 5 | 11% |
| Professor | 4 | 9% |
| Student > Bachelor | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 5 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 37% |
| Biochemistry, Genetics and Molecular Biology | 15 | 33% |
| Chemistry | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Computer Science | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 6 | 13% |