Table 3 Comparison of our machine learning method and Flux Balance Analyses on glucose minimal media condition
From: Machine learning based analyses on metabolic networks supports high-throughput knockout screens
Performance | ML\BFV1 | ML2 | FBA3 |
|---|---|---|---|
true positives | 192 | 266 | 174 |
true negatives | 932 | 968 | 971 |
false positives | 64 | 28 | 25 |
false negatives | 146 | 72 | 164 |
sensitivity | 56.80% | 78.70% | 51.48% |
specificity | 93.57% | 97.19% | 97.49% |
positive predictive values | 75.00% | 90.48% | 87.44% |
negative predictive values | 86.46% | 93.08% | 85.55% |
overall accuracy | 84.26% | 92.50% | 85.83% |