Configuration

MixingDTA (retrained on Davis and KIBA, PLABench)

Configuration of MixingDTA: Retrained by the benchmark authors on Davis or KIBA under each split (warm: 5-fold CV on an 80/20 split; cold splits: two-stage protocol from MixingDTA, five fold models evaluated on a fixed test set and aggregated).

6 evaluations · 36 results

Overview

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Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

6 evaluations · 36 results. Different protocols are not a single leaderboard.

Sorted by Concordance index (PLABench Davis-cold-drug) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Protocol and dataset	Concordance index (PLABench Davis-cold-drug)	Concordance index (PLABench Davis-cold-target)	Concordance index (PLABench Davis-warm)	Concordance index (PLABench KIBA-cold-drug)	Concordance index (PLABench KIBA-cold-target)	Concordance index (PLABench KIBA-warm)	Modified squared correlation (PLABench Davis-cold-drug)	Modified squared correlation (PLABench Davis-cold-target)	Modified squared correlation (PLABench Davis-warm)	Modified squared correlation (PLABench KIBA-cold-drug)	Modified squared correlation (PLABench KIBA-cold-target)	Modified squared correlation (PLABench KIBA-warm)	MSE (PLABench Davis-cold-drug)	MSE (PLABench Davis-cold-target)	MSE (PLABench Davis-warm)	MSE (PLABench KIBA-cold-drug)	MSE (PLABench KIBA-cold-target)	MSE (PLABench KIBA-warm)	Pearson (PLABench Davis-cold-drug)	Pearson (PLABench Davis-cold-target)	Pearson (PLABench Davis-warm)	Pearson (PLABench KIBA-cold-drug)	Pearson (PLABench KIBA-cold-target)	Pearson (PLABench KIBA-warm)	RMSE (PLABench Davis-cold-drug)	RMSE (PLABench Davis-cold-target)	RMSE (PLABench Davis-warm)	RMSE (PLABench KIBA-cold-drug)	RMSE (PLABench KIBA-cold-target)	RMSE (PLABench KIBA-warm)	Spearman (PLABench Davis-cold-drug)	Spearman (PLABench Davis-cold-target)	Spearman (PLABench Davis-warm)	Spearman (PLABench KIBA-cold-drug)	Spearman (PLABench KIBA-cold-target)	Spearman (PLABench KIBA-warm)
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench Davis, cold-drug split, Davis cold-drug test set (PLABench)	0.738	Not reported	Not reported	Not reported	Not reported	Not reported	0.211	Not reported	Not reported	Not reported	Not reported	Not reported	0.54	Not reported	Not reported	Not reported	Not reported	Not reported	0.515	Not reported	Not reported	Not reported	Not reported	Not reported	0.735	Not reported	Not reported	Not reported	Not reported	Not reported	0.447	Not reported	Not reported	Not reported	Not reported	Not reported
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench Davis, cold-target split, Davis cold-target test set (PLABench)	Not reported	0.841	Not reported	Not reported	Not reported	Not reported	Not reported	0.485	Not reported	Not reported	Not reported	Not reported	Not reported	0.292	Not reported	Not reported	Not reported	Not reported	Not reported	0.727	Not reported	Not reported	Not reported	Not reported	Not reported	0.541	Not reported	Not reported	Not reported	Not reported	Not reported	0.586	Not reported	Not reported	Not reported	Not reported
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench Davis, warm split, Davis warm test set (PLABench)	Not reported	Not reported	0.89	Not reported	Not reported	Not reported	Not reported	Not reported	0.678	Not reported	Not reported	Not reported	Not reported	Not reported	0.213	Not reported	Not reported	Not reported	Not reported	Not reported	0.83	Not reported	Not reported	Not reported	Not reported	Not reported	0.462	Not reported	Not reported	Not reported	Not reported	Not reported	0.681	Not reported	Not reported	Not reported
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench KIBA, cold-drug split, KIBA cold-drug test set (PLABench)	Not reported	Not reported	Not reported	0.756	Not reported	Not reported	Not reported	Not reported	Not reported	0.432	Not reported	Not reported	Not reported	Not reported	Not reported	0.34	Not reported	Not reported	Not reported	Not reported	Not reported	0.68	Not reported	Not reported	Not reported	Not reported	Not reported	0.583	Not reported	Not reported	Not reported	Not reported	Not reported	0.65	Not reported	Not reported
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench KIBA, cold-target split, KIBA cold-target test set (PLABench)	Not reported	Not reported	Not reported	Not reported	0.761	Not reported	Not reported	Not reported	Not reported	Not reported	0.502	Not reported	Not reported	Not reported	Not reported	Not reported	0.358	Not reported	Not reported	Not reported	Not reported	Not reported	0.712	Not reported	Not reported	Not reported	Not reported	Not reported	0.598	Not reported	Not reported	Not reported	Not reported	Not reported	0.656	Not reported
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	PLABench KIBA, warm split, KIBA warm test set (PLABench)	Not reported	Not reported	Not reported	Not reported	Not reported	0.878	Not reported	Not reported	Not reported	Not reported	Not reported	0.757	Not reported	Not reported	Not reported	Not reported	Not reported	0.163	Not reported	Not reported	Not reported	Not reported	Not reported	0.876	Not reported	Not reported	Not reported	Not reported	Not reported	0.404	Not reported	Not reported	Not reported	Not reported	Not reported	0.871

All 36 result rows with coverage, uncertainty and sources

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.738 Concordance index (PLABench Davis-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'CI' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.54 MSE (PLABench Davis-cold-drug) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'MSE' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.515 Pearson (PLABench Davis-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'Pearson' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.211 Modified squared correlation (PLABench Davis-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'rm2' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.735 RMSE (PLABench Davis-cold-drug) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'RMSE' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-drug split Dataset: Davis cold-drug test set (PLABench)	0.447 Spearman (PLABench Davis-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-drug lit-interactions-20261011-leakctl-protocol-davis-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'Davis', column 'Spearman' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.841 Concordance index (PLABench Davis-cold-target) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'CI' (text-layer line 444)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.292 MSE (PLABench Davis-cold-target) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'MSE' (text-layer line 444)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.727 Pearson (PLABench Davis-cold-target) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'Pearson' (text-layer line 444)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.485 Modified squared correlation (PLABench Davis-cold-target) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'rm2' (text-layer line 444)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.541 RMSE (PLABench Davis-cold-target) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'RMSE' (text-layer line 444)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench Davis, cold-target split Dataset: Davis cold-target test set (PLABench)	0.586 Spearman (PLABench Davis-cold-target) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench Davis-cold-target lit-interactions-20261011-leakctl-protocol-davis-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'Davis', column 'Spearman' (text-layer line 444)
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 checked Methods, coverage and source MixingDTA 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 checked Methods, coverage and source MixingDTA 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 checked Methods, coverage and source MixingDTA 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 checked Methods, coverage and source MixingDTA 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 checked Methods, coverage and source MixingDTA 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 checked Methods, coverage and source MixingDTA 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)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.756 Concordance index (PLABench KIBA-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'CI' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.34 MSE (PLABench KIBA-cold-drug) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'MSE' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.68 Pearson (PLABench KIBA-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'Pearson' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.432 Modified squared correlation (PLABench KIBA-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'rm2' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.583 RMSE (PLABench KIBA-cold-drug) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'RMSE' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-drug split Dataset: KIBA cold-drug test set (PLABench)	0.65 Spearman (PLABench KIBA-cold-drug) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-drug lit-interactions-20261011-leakctl-protocol-kiba-cold-drug Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-drug', dataset 'KIBA', column 'Spearman' (text-layer line 447)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, cold-target split Dataset: KIBA cold-target test set (PLABench)	0.761 Concordance index (PLABench KIBA-cold-target) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-cold-target lit-interactions-20261011-leakctl-protocol-kiba-cold-target Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Cold-target', dataset 'KIBA', column 'CI' (text-layer line 444)

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Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Original source · bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF

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Technical metadata and extraction receipts

Stable ID: lit-interactions-20261011-leakctl-config-mixingdta-davis-kiba

areas: molecular-interactions
contexts: research
method types: foundation_model
reported name: MixingDTA
foundation model eligible: true
parameters: Retrained by the benchmark authors on Davis or KIBA under each split (warm: 5-fold CV on an 80/20 split; cold splits: two-stage protocol from MixingDTA, five fold models evaluated on a fixed test set and aggregated)
source locator: Table 1; Methods; Table 2
access reuse: Not stated per model in the source; see each model's release
missing metadata: version: reason: unreported; note: No checkpoint version printed
provenance note: MixingDTA as evaluated in PLABench (sequence-based).

Related records

configuration of: MixingDTA
system: MixingDTA on PLABench Davis-cold-drug
system: MixingDTA on PLABench Davis-cold-target
system: MixingDTA on PLABench Davis-warm
system: MixingDTA on PLABench KIBA-cold-drug
system: MixingDTA on PLABench KIBA-cold-target
system: MixingDTA on PLABench KIBA-warm

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