<p>(A) The ROC curve illustrating the performance for full transcript mode. (B) The ROC curve illustrating the performance for mature mRNA mode.</p
(a) ROC curves for classification of liver enhancers vs. the genomic background in six diverse mamma...
<p>Performance is measured with leave-one-protein-out cross-validation using the area under the ROC ...
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>(A) ROC curve illustrating the performance on the unbalanced independent testing dataset in full ...
<p>(A) ROC curve for the HIV-RT classifier. (B) ROC curve for the adenosine receptors classifier. (C...
<p>Results are evaluated based on the benchmark dataset (A) and independent test dataset (B).</p
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>The ROC curve showing the tradeoff between the True Positive Rate (sensitivity) and the False Pos...
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
(A)Training data performances over a 10-fold cross-validation test. (B) Test dataset performances.</...
<p>The standard deviations are computed from a five-fold cross validation.</p><p>Classification perf...
<p>ROC-curves of composition-based classifiers using the codon sequence (), the signal peptide seque...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
(a) ROC curves for classification of liver enhancers vs. the genomic background in six diverse mamma...
<p>Performance is measured with leave-one-protein-out cross-validation using the area under the ROC ...
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>(A) ROC curve illustrating the performance on the unbalanced independent testing dataset in full ...
<p>(A) ROC curve for the HIV-RT classifier. (B) ROC curve for the adenosine receptors classifier. (C...
<p>Results are evaluated based on the benchmark dataset (A) and independent test dataset (B).</p
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>The ROC curve showing the tradeoff between the True Positive Rate (sensitivity) and the False Pos...
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
(A)Training data performances over a 10-fold cross-validation test. (B) Test dataset performances.</...
<p>The standard deviations are computed from a five-fold cross validation.</p><p>Classification perf...
<p>ROC-curves of composition-based classifiers using the codon sequence (), the signal peptide seque...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
(a) ROC curves for classification of liver enhancers vs. the genomic background in six diverse mamma...
<p>Performance is measured with leave-one-protein-out cross-validation using the area under the ROC ...
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
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