Table 2.
Per-protein predictions: localization and membrane/globular
| Method | Localization | Membrane/globular | ||
|---|---|---|---|---|
| Q10 (%) | Gorodkin (MCC) | Q2 | MCC | |
| LocTree2a,b | 61 | 0.53 | ||
| MultiLoc2a,b | 56 | 0.49 | ||
| CELLOa | 55 | 0.45 | ||
| WoLF PSORTa | 57 | 0.48 | ||
| YLoca | 61 | 0.53 | ||
| SherLoc2a,b | 58 | 0.51 | ||
| iLoc-Euka,b | 68 | 0.64 | ||
| DeepLoca,b | 78 | 0.73 | 92.3 | 0.844 |
| DeepSeqVec-Loc | 68 ± 1 | 0.61 ± 0.01 | 86.8 ± 1.0 | 0.725 ± 0.021 |
| DeepProtVec-Loc | 42 ± 1 | 0.19 ± 0.01 | 77.6 ± 1.3 | 0.531 ± 0.026 |
Performance for per-protein prediction of subcellular localization and classifying proteins into membrane-bound and water-soluble. Results marked by a taken from DeepLoc [47]; the authors provided no standard errors. The results reported for SeqVec and ProtVec were based on single protein sequences, i.e. methods NOT using evolutionary information (neither during training nor testing). All methods using evolutionary information are marked by b; best in each set marked by bold numbers