| Configuration: ProkBERT-mini | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.87 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini: E. coli sigma70 promoter prediction Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications; ProkBERT family: genomic language models for microbiome applications · Table 3, ProkBERT-mini row, Accuracy column |
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| Configuration: Promotech | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.71 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcePromotech: E. coli sigma70 promoter prediction Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications; ProkBERT family: genomic language models for microbiome applications · Table 3, Promotech row, Accuracy column |
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| Configuration: Sigma70Pred | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.66 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSigma70Pred: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row Sigma70Pred, column Accuracy; XML row14 column2 |
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| Configuration: ProkBERT-mini-long | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.89 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini-long: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini-long, column Sensitivity; XML row4 column4 |
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| Configuration: Promotech | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.49 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcePromotech: E. coli sigma70 promoter prediction Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row Promotech, column Sensitivity; XML row13 column4 |
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| Configuration: CNNProm | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.51 Specificity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceCNNProm: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row CNNProm, column Specificity; XML row5 column5 |
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| Configuration: iPromoter-2L | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.64 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceiPromoter-2L: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPromoter-2L, column Accuracy; XML row8 column2 |
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| Configuration: 70ProPred | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.74 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and source70ProPred: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row 70ProPred, column Accuracy; XML row7 column2 |
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| Configuration: bTSSfinder | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.46 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourcebTSSfinder: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row bTSSfinder, column Accuracy; XML row10 column2 |
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| Configuration: BPROM | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.1 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceBPROM: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row BPROM, column MCC; XML row11 column3 |
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| Configuration: ProkBERT-mini | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.9 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini: E. coli sigma70 promoter prediction Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini, column Sensitivity; XML row2 column4 |
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| Configuration: iPromoter-BnCNN | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.18 Specificity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceiPromoter-BnCNN: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPromoter-BnCNN, column Specificity; XML row15 column5 |
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| Configuration: IBPP | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | -0.03 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceIBPP: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row IBPP, column MCC; XML row12 column3 |
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| Configuration: ProkBERT-mini | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.85 Specificity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini: E. coli sigma70 promoter prediction Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini, column Specificity; XML row2 column5 |
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| Configuration: iPromoter-2L | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.37 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceiPromoter-2L: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPromoter-2L, column MCC; XML row8 column3 |
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| Configuration: 70ProPred | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.51 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and source70ProPred: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row 70ProPred, column MCC; XML row7 column3 |
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| Configuration: ProkBERT-mini-c | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.88 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini-c: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini-c, column Sensitivity; XML row3 column4 |
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| Configuration: iPro70-FMWin | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.76 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceiPro70-FMWin: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPro70-FMWin, column Accuracy; XML row6 column2 |
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| Configuration: MULTiPly | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.92 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMULTiPly: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row MULTiPly, column Sensitivity; XML row16 column4 |
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| Configuration: ProkBERT-mini-c | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.85 Specificity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini-c: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini-c, column Specificity; XML row3 column5 |
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| Configuration: iPromoter-2L | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.37 Specificity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceiPromoter-2L: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPromoter-2L, column Specificity; XML row8 column5 |
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| Configuration: iPro70-FMWin | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.53 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceiPro70-FMWin: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row iPro70-FMWin, column MCC; XML row6 column3 |
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| Configuration: Multiply | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.05 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceMultiply: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row Multiply, column MCC; XML row9 column3 |
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| Configuration: Multiply | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.81 Sensitivity fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Result quoted from another source · Source checkedMethods, coverage and sourceMultiply: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row Multiply, column Sensitivity; XML row9 column4 |
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| Configuration: ProkBERT-mini-long | Protocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction) Dataset: E. coli sigma70 promoter dataset | 0.87 Accuracy unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceProkBERT-mini-long: E. coli sigma70 independent promoter test Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Aggregation: Not reported ProkBERT family: genomic language models for microbiome applications · Table 3, row ProkBERT-mini-long, column Accuracy; XML row4 column2 |
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