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Mendeley readers
Title |
MeDor: a metaserver for predicting protein disorder
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Published in |
BMC Genomics, September 2008
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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% |