Gene Ontology Prediction on Gene Ontology
49BP ScoreGearNet-E-IE with MC
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| GearNet-E-IE with MCPretraining Dataset=AlphaFoldDB 805K2026.06 | 49 | 65.4 | 48.8 | |
| ESM-1bPretraining Dataset=UniRef50 24M2026.06 | 47 | 65.7 | 48.8 | |
| IEConv (Residue Level)Pretraining Dataset=PDB 476K2026.06 | 46.8 | 66.1 | 51.6 | |
| SaProt-PDBPretraining Dataset=PDB 60K2026.06 | 46.5 | 66.9 | 41.5 | |
| CDConv w/ MRMInput Dimensionality=(3+1)D, MRM=true2026.06 | 46.2 | 66.7 | 49.6 | |
| CDConv w/ MRMPretraining Dataset=-2026.06 | 46.2 | 66.7 | 49.6 | |
| ESM-2Pretraining Dataset=UniRef50 24M2026.06 | 46 | 66.1 | 44.5 | |
| GearNet-E-IE with APPretraining Dataset=AlphaFoldDB 805K2026.06 | 45.8 | 62.5 | 47.3 | |
| GearNet-E-IE with DPPretraining Dataset=AlphaFoldDB 805K2026.06 | 45.8 | 62.6 | 46.5 | |
| CDConvInput Dimensionality=(3+1)D2026.06 | 45.3 | 65.4 | 47.9 | |
| GearNet-E-IE with DPPretraining Dataset=AlphaFoldDB 805K2026.06 | 44.8 | 61.6 | 46.4 | |
| GearNet-E-IE with RTPPretraining Dataset=AlphaFoldDB 805K2026.06 | 43 | 60.4 | 46.5 | |
| LM-GVPPretraining Dataset=UniRef100 0.21B2026.06 | 41.7 | 54.5 | 52.7 | |
| GearNet-Edge w/ MRMInput Dimensionality=(3+1)D, MRM=true2026.06 | 41.2 | 59.1 | 46.3 | |
| GearNet-EdgeInput Dimensionality=(3+1)D2026.06 | 40.3 | 58 | 45 | |
| DeepFRIPretraining Dataset=Pfam 10M2026.06 | 39.9 | 46.5 | 46 | |
| New IEConvInput Dimensionality=(3+1)D2026.06 | 37.4 | 54.4 | 44.4 | |
| GearNet w/ MRMInput Dimensionality=(3+1)D, MRM=true2026.06 | 36.8 | 51.4 | 42.6 | |
| GearNetInput Dimensionality=(3+1)D2026.06 | 35.6 | 50.3 | 41.4 | |
| GVPInput Dimensionality=(3+1)D2026.06 | 32.6 | 42.6 | 42 | |
| GraphQAInput Dimensionality=(3+1)D2026.06 | 30.8 | 32.9 | 41.3 | |
| GATInput Dimensionality=3D2026.06 | 28.4 | 31.7 | 38.5 | |
| ResNetInput Dimensionality=1D2026.06 | 28 | 40.5 | 30.4 | |
| ProtBERT-BFDPretraining Dataset=BFD 2.1B2026.06 | 27.9 | 45.6 | 40.8 | |
| TransformerInput Dimensionality=1D2026.06 | 26.4 | 21.1 | 40.5 | |
| GCNInput Dimensionality=3D2026.06 | 25.2 | 19.5 | 32.9 | |
| CNNInput Dimensionality=1D2026.06 | 24.4 | 35.4 | 28.7 | |
| 3DCNNInput Dimensionality=3D2026.06 | 24 | 14.7 | 30.5 | |
| LSTMInput Dimensionality=1D2026.06 | 22.5 | 32.1 | 28.3 |