8 research outputs found
The predictive probability plot of screening all cross-linking drug-target pairs. The size of predictive probability gradually varies from green to red.
<p>The predictive probability plot of screening all cross-linking drug-target pairs. The size of predictive probability gradually varies from green to red.</p
ROCs and precision-recall curves for Naïve Bayes (green) and random forest (red) with full and selected features.
<p>(A) ROCs (B) precision-recall curves.</p
Prediction results of five-fold cross validation using different models.
<p>TP: true positives; FN: false negatives; TN: true negatives; FP: false positives; Sen: sensitivity; Spe: specificity; Acc: accuracy.</p
Drug-target interaction network using drug-target pairs with prediction probability above 0.99.
<p>Drugs and targets are presented by red circle and blue triangle, respectively. Drug-target interactions are represented by the edges connecting related drugs and targets.</p
The plot of K<sub>i</sub> versus prediction probability on 5-fold cross validation.
<p>non-interaction: red and interaction: green. Linear relationship between K<sub>i</sub> and prediction probability could be observed with correlation coefficient of 0.65.</p
ROCs and precision-recall curves with different K<sub>i</sub> thresholds using RF.
<p>(A) ROCs (B) precision-recall curves. The auPRCs drop with the decreasing of K<sub>i</sub> thresholds. However, the varying trend of auROCs is consistent with that of auPRCs.</p
Outline of our methodology.
<p>(A) Interaction features are calculated by combing the fingerprint descriptors from drugs and the CTD and amino acid composition descriptors from protein sequences. These feature vectors are used to find the optimal RF parameters which most accurately separate the positive and negative training sets. The independent validation sets are used for further validation for the RF model. (B) Once the RF model is constructed, we can predict new unknown drug-target associations or screen all cross-linking associations.</p
Prediction statistics on different false discovery rates.
<p>FDR: false discovery rate, Number: Number of drug-target pairs predicted as interactions, Ratio: the ratio between drug target pairs predicted as interactions and all screening pairs on specific FDR.</p