E 3 A A g Time s 'r r a E A AA Time Time | The FWER is the probability that there is at least one false positive for a given threshold. |
E 3 A A g Time s 'r r a E A AA Time Time | Therefore, a threshold of 0.01 means that there is a 1% chance that the list of time series with a Bonferroni adjusted p-value below 0.01 contains a false positive . |
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 | 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 | The TPR and FPR are the fractions of the 10,000 simulated or Gaussian noise time series determined to be rhythmic at a threshold, respectively, and the threshold is varied over the entire range of false positive scores, such that the FPR ranges from 0 to 1. |
Simulated data benchmarks | In such cases, we find that ANOVA, F24, and ITK_CYCLE consistently better distinguish true and false positives . |
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 | It is important to note that both the precision and coverage of our method depend dramatically on the definition of false positives for our predictions. |
nAnnoLyze prediction examples | Aspirin (DB00945), also a known inhibitor of the human COX-1 and COX-2, results in false positive predictions (Table 4 and Fig. |
nAnnoLyze prediction examples | The same pathway is used to find other proteases like the Airway trypsin-like protease 4 (Q6ZWK6) or the Trypsin-3 (P35030) resulting in several false positive predictions. |