| Configuration: I-Mutant3.0-Seq (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 | –0.48 pearson-correlation unitless · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Antisimmetry r(d-r)' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | –0.76 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Bias' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 1.15 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Direct MAE' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 0.34 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Direct r' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 1.54 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Direct RMSE' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 1.79 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Reverse MAE' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 0.22 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Reverse r' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 2.22 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Reverse RMSE' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 1.47 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Total MAE' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 0.37 pearson-correlation unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Total r' |
|---|
| Configuration: I-Mutant3.0-Seq (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 | 1.91 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 sourceI-Mutant3.0-Seq 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 'I-Mutant3.0-Seq', column 'Total RMSE' |
|---|