Table 3 Results of the applications of network inference algorithms on the experimental datasets
From: Recursive regularization for inferring gene networks from time-course gene expression profiles
Method | EGF | HRG | ||||
|---|---|---|---|---|---|---|
TP | TDR | p-value | TP | TDR | p-value | |
RAND | 8.73 | 0.05 | - | 8.29 | 0.05 | |
MRN | 8 | 0.05 | 0.65 | 8 | 0.05 | 0.59 |
CLR | 4 | 0.03 | 0.98 | 7 | 0.05 | 0.73 |
ARA | 9 | 0.06 | 0.51 | 7 | 0.05 | 0.73 |
MRN-L | 12 | 0.08 | 0.16 | 10 | 0.07 | 0.32 |
CLR-L | 6 | 0.04 | 0.87 | 9 | 0.06 | 0.45 |
ARA-L | 6 | 0.04 | 0.87 | 9 | 0.06 | 0.45 |
JS | 6 | 0.04 | 0.87 | 8 | 0.05 | 0.59 |
LA | 9 | 0.06 | 0.51 | 7 | 0.05 | 0.73 |
NEN | 10 | 0.06 | 0.38 | 9 | 0.06 | 0.45 |
EN | 8 | 0.05 | 0.65 | 17 | 0.11 | 4.0 × 10-3 |
REN | 16 | 0.10 | 0.01 | 19 | 0.13 | 6.7 × 10-4 |
CREN | 11 | 0.07 | 0.25 | 16 | 0.11 | 8.8 × 10-3 |