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Mendeley readers
| Title |
Is EC class predictable from reaction mechanism?
|
|---|---|
| Published in |
BMC Bioinformatics, April 2012
|
| DOI | 10.1186/1471-2105-13-60 |
| Pubmed ID | |
| Authors |
Neetika Nath, John BO Mitchell |
| Abstract |
We investigate the relationships between the EC (Enzyme Commission) class, the associated chemical reaction, and the reaction mechanism by building predictive models using Support Vector Machine (SVM), Random Forest (RF) and k-Nearest Neighbours (kNN). We consider two ways of encoding the reaction mechanism in descriptors, and also three approaches that encode only the overall chemical reaction. Both cross-validation and also an external test set are used. |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 3 | 5% |
| United Kingdom | 2 | 4% |
| Brazil | 1 | 2% |
| France | 1 | 2% |
| Austria | 1 | 2% |
| Thailand | 1 | 2% |
| Unknown | 47 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 38% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Master | 6 | 11% |
| Professor > Associate Professor | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Other | 12 | 21% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 23% |
| Biochemistry, Genetics and Molecular Biology | 8 | 14% |
| Computer Science | 8 | 14% |
| Chemistry | 6 | 11% |
| Medicine and Dentistry | 5 | 9% |
| Other | 9 | 16% |
| Unknown | 7 | 13% |