Table 2. Performance of the Literature Reference Set, the Extended Reference Set, the Individual Reverse-Engineering Methods, and Their Ensemble Solutions on Correctly Predicting the NanoString nCounter Experimental Data.
| Npred | Nknown | TP | Precision | Recall | F | |
|---|---|---|---|---|---|---|
| Literature reference set | 7 | 289 | 6 | 0.857 | 0.021 | 0.041 |
| Extended reference set | 192 | 289 | 94 | 0.490 | 0.325 | 0.391 |
| LeMoNe_qopt25R | 155 | 289 | 78 | 0.503 | 0.270 | 0.351 |
| LemoNe_qopt50R | 136 | 289 | 60 | 0.441 | 0.208 | 0.282 |
| ClrR | 195 | 289 | 96 | 0.492 | 0.332 | 0.397 |
| Union | 172 | 289 | 84 | 0.488 | 0.291 | 0.364 |
| Rank_rp | 177 | 289 | 86 | 0.486 | 0.298 | 0.369 |
| Rank_av | 199 | 289 | 100 | 0.503 | 0.346 | 0.410 |
| All_pred | 249 | 289 | 125 | 0.502 | 0.433 | 0.465 |
| Rank_av_2 | 271 | 289 | 141 | 0.520 | 0.488 | 0.504 |
| ERF6 | 11 | 49 | 10 | 0.909 | 0.204 | 0.333 |
| NAC13 | 30 | 85 | 27 | 0.900 | 0.318 | 0.470 |
| NAC032 | 41 | 42 | 22 | 0.537 | 0.524 | 0.530 |
| NAC053 | 32 | 57 | 13 | 0.406 | 0.228 | 0.292 |
| RAP2.1 | 18 | 6 | 2 | 0.111 | 0.333 | 0.167 |
| RAP2.6L | 26 | 4 | 3 | 0.115 | 0.750 | 0.200 |
| WRKY6 | 41 | 46 | 23 | 0.561 | 0.500 | 0.529 |
| ERF6_2 | 13 | 49 | 11 | 0.846 | 0.224 | 0.355 |
| NAC13_2 | 32 | 85 | 29 | 0.906 | 0.341 | 0.496 |
| NAC032_2 | 61 | 42 | 35 | 0.574 | 0.833 | 0.680 |
| NAC053_2 | 52 | 57 | 23 | 0.442 | 0.404 | 0.422 |
| WRKY6_2 | 69 | 46 | 38 | 0.551 | 0.826 | 0.661 |
The table shows the literature reference set of 52,328 experimental protein-DNA and regulatory interactions, the extended reference set, the top 200,000 predictions of the individual reverse-engineering methods LeMoNe_qopt25R, LeMoNe_qopt50R, and ClrR, and their ensemble solutions by union (Union), mean reciprocal rank (Rank_rp), and average rank (Rank_av) aggregation, against the 289 NanoString nCounter experimental data. The “_2” also takes the predictions of the TF targets of the perturbed TFs into account (paths of length two). For the final abiotic stress gene regulatory network (Rank_av and Rank_av_2; underlined), each TF was also evaluated individually. All_pred points to the 785,913 predictions of all four individual inference methods. Npred = number of predictions made for TFs and target genes belonging to the nCounter experimental data; Nknown = number of experimental nCounter interactions; TP = number of true positives; Precision = TP/Npred; Recall = TP/Nknown; F = 2 × precision × recall/(precision + recall) = 2 × TP/(2 × TP + FP + FN).