Table 2.
PHENSIM proteomic predicted values from Bojkova et al. 2020.
| Time (hours) | All Proteins | Proteins in Meta-pathway | Predicted Percentage |
Accuracy | PPV | Sensitivity | Specificity |
|---|---|---|---|---|---|---|---|
| 2 | 5809 | 1914 | 6.95% | 93.98% | 95.45% | 92.65% | 95.38% |
| 6 | 5809 | 1914 | 11.70% | 93.75% | 94.35% | 97.66% | 81.13% |
| 10 | 5809 | 1914 | 10.45% | 94.50% | 95.27% | 98.17% | 77.78% |
| 24 | 5809 | 1914 | 34.95% | 97.91% | 98.39% | 97.87% | 97.96% |
All Proteins; number (N) of proteins quantified for each timepoint.
Proteins in Meta-pathway; number (N) of proteins present in KEGG, and therefore in the meta-pathway. Predicted Percentage; Percent (%) proteins for which PHENSIM could produce a prediction.
Accuracy, PPV, Sensitivity, and Specificity; the metrics used to compare our model with the actual proteomics data. PPV; Positive predictive value. Bojkova et al., Nature 2020 [9].