E 3 A A g Time s 'r r a E A AA Time Time | The likelihood of false positives is greatly reduced, but so is the likelihood of identifying true positives . |
Simulated data benchmarks | We use it to further assess the importance of considering asymmetric waveforms, and we eXplore how multiple hypothesis correction impacts the results when the true positives represent a relatively small fraction of the simulated time series, as we eXpect to be the case in genome-wide studies. |
Simulated data benchmarks | The receiver operating characteristic (ROC) curve plots the true positive rate (TPR) as a function of the false positive rate (FPR) as the threshold for calling a time series as a positive is varied. |
Simulated data benchmarks | A score of 1 indicates that a method correctly identified all true positives and true negatives, while a score of —1 indicates that a method yielded all false positives and false negatives. |
Discussion | Within the correctly predicted interactions (i.e., true positives ), we included Flurbiprofen and Ibuprofen detailed information about the network routes. |
nAnnoLyze benchmark | First, the precision defined as the ratio between the true positives (TP; true drug-protein interactions found by nAnno-Lyze) and the sum of TP and false positives (FP, a link between a drug and a protein not in the PDB). |
nAnnoLyze benchmarking | 1A) with an optimal threshold at —2.5 local Z-score resulting in a precision of 0.63 and coverage of 0.19 corresponding to 1,148 true positive predictions (Fig. |