Table 4 |
|
| SVM classification using different data sources | |
| Data source | AUC |
| AmiGO | 0.886 |
| BioCyc | 0.807 |
| CDD | 0.876 |
| GenNav | 0.940 |
| InterPro | 0.883 |
| Kegg | 0.795 |
| Kegg (pathways) | 0.815 |
| Pdb | 0.875 |
| TigrFam | 0.872 |
Above are results by source, when empty graphs (query graphs with no returned results) are excluded from training and testing; the scores are thus those of each source given data from that source was available.
Cadag et al. BMC Bioinformatics 2012 13:321 doi:10.1186/1471-2105-13-321
