| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | –0.97 pearson-correlation unitless · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Antisimmetry r(d-r)' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | –0.05 antisymmetry-bias kilocalorie-per-mole · unknown Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Bias' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.11 mean-absolute-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Direct MAE' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 0.43 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Direct r' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.6 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Direct RMSE' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.14 mean-absolute-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Reverse MAE' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 0.41 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Reverse r' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.62 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Reverse RMSE' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.13 mean-absolute-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Total MAE' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 0.57 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Total r' |
|---|
| Configuration: DDGun3D (Pancotti et al. 2022) | Protocol: S669 direct and reverse ddG prediction (Pancotti et al. 2022 Table 1)
Dataset: S669: 669 single-point variants from ThermoMutDB in proteins under 25% identity to S2648 and VariBench, with reverse variants | 1.61 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDDGun3D on S669 (Pancotti et al. 2022) protein-stability-20261009-protocol-pancotti2022-s669 Aggregation: Not reported Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset · Table 1, row 'DDGun3D', column 'Total RMSE' |
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