<p>(Class A: the selected 30 genes; Class B: the other genes) using the 4 different approaches: (1) SAM; (2) Normal graph strategy (NGS); (3) Decision Tree (DT); (4) weighted graph strategy (WGS).</p
<p>ROC curves found for <i>a priori</i> manifold learning (blue) compared with PCA (Green) and Isoma...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
<p>(A) ROC curve of the 349-gene predictive model in training set (200 samples, AUC = 0.826; <i>p<</...
<p>(A) ROC curves for Gram-negative dataset. (B) ROC curves for Gram-positive dataset. (C) ROC curve...
ROC curves are plotted using 10 randomly selected training and testing data sets using 80%, and 20% ...
<p>ROC curve analysis for evaluating the effectiveness of the selected experiments at improving the ...
<div><p>(A) Lack of correlation between score.20 and other measures.</p><p>(B) Diagram of the analyt...
<p>(a) first ROC: Class 1 – four-fold NP differentially over-expressed genes compared to ES; Class 0...
<p>TARGETgene prediction performance is evaluated by genes in the identified core pathways.</p
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>ROC curves of the residual variation intolerance scores' capacity to predict the corresponding in...
<p>(a) shows genes contained in the integrated BRCA pathway, (c) shows genes contained in the GBM KE...
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>ROC curves found for <i>a priori</i> manifold learning (blue) compared with PCA (Green) and Isoma...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
<p>(A) ROC curve of the 349-gene predictive model in training set (200 samples, AUC = 0.826; <i>p<</...
<p>(A) ROC curves for Gram-negative dataset. (B) ROC curves for Gram-positive dataset. (C) ROC curve...
ROC curves are plotted using 10 randomly selected training and testing data sets using 80%, and 20% ...
<p>ROC curve analysis for evaluating the effectiveness of the selected experiments at improving the ...
<div><p>(A) Lack of correlation between score.20 and other measures.</p><p>(B) Diagram of the analyt...
<p>(a) first ROC: Class 1 – four-fold NP differentially over-expressed genes compared to ES; Class 0...
<p>TARGETgene prediction performance is evaluated by genes in the identified core pathways.</p
A) ROC curves for compound-wise rankings (gray curves) and compound-aggregated rankings (coloured cu...
<p>ROC curves of the residual variation intolerance scores' capacity to predict the corresponding in...
<p>(a) shows genes contained in the integrated BRCA pathway, (c) shows genes contained in the GBM KE...
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>ROC curves found for <i>a priori</i> manifold learning (blue) compared with PCA (Green) and Isoma...
(A) Prediction of “Benign” broader class versus “Pathogenic” broader class and “VUS” class (B) Predi...
<p>(A) ROC curve of the 349-gene predictive model in training set (200 samples, AUC = 0.826; <i>p<</...
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