Davis kinase binding affinities (pKd), random partition (warm split) as established by MixingDTA.
3 evaluations · 18 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.875 Concordance index (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'CI' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.232 MSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'MSE' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.816 Pearson (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'Pearson' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.625 Modified squared correlation (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'rm2' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.482 RMSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'RMSE' (text-layer line 439) |
| Configuration: DeepDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.658 Spearman (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'Davis', column 'Spearman' (text-layer line 439) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.881 Concordance index (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'CI' (text-layer line 440) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.224 MSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'MSE' (text-layer line 440) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.821 Pearson (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'Pearson' (text-layer line 440) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.656 Modified squared correlation (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'rm2' (text-layer line 440) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.473 RMSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'RMSE' (text-layer line 440) |
| Configuration: LLF (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.669 Spearman (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcelit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'Davis', column 'Spearman' (text-layer line 440) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.89 Concordance index (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'CI' (text-layer line 441) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.213 MSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'MSE' (text-layer line 441) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.83 Pearson (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'Pearson' (text-layer line 441) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.678 Modified squared correlation (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'rm2' (text-layer line 441) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.462 RMSE (PLABench Davis-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'RMSE' (text-layer line 441) |
| Configuration: MixingDTA (retrained on Davis and KIBA, PLABench) | Protocol: PLABench Davis, warm split Dataset: Davis warm test set (PLABench) | 0.681 Spearman (PLABench Davis-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMixingDTA on PLABench Davis-warm lit-interactions-20261011-leakctl-protocol-davis-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'Davis', column 'Spearman' (text-layer line 441) |
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6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Population Standardised Davis: 25,772 pairs, 379 unique sequences, 68 ligands (Methods lines 363-369) Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Source location Table 2; Methods 'Datasets' Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Split random partition (warm split) as established by MixingDTA Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Version Davis as split by MixingDTA (PLABench) Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Davis kinase binding affinities (pKd), random partition (warm split) as established by MixingDTA. Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Name Davis warm test set (PLABench) Context-only references | Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction Table 2; Methods 'Datasets' Version: bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-10-23-5347695500ed · Record review: source checked
Stable ID: lit-interactions-20261011-leakctl-data-davis-warm