Table 2. An overview of the characteristics of all case studies approached in this work.
case study | Short name | Reference | Data | Nobs | N Train | N Prediction | deg−(vi) |
---|---|---|---|---|---|---|---|
1a | MAPKp | [67] | in silico | 4 | 10 | 10 | A = 1, B = 2, C = 3 |
1b | MAPKf | [67] | in silico | 13 | 10 | 10 | A = 3, B = 4, C = 5 |
2 | SSP | [68] | in silico | 13 | 10 | 36 | A = 3, B = 4, C = 5 |
3 | DREAMiS | [69] | in silico | 2 | 20 | 128 | A = 3, B = 4, C = 5 |
4a | DREAMBT20 | [70] | Experimental | 54 | 29 | 8 | A = 3, B = 4, C = 5 |
4b | DREAMBT549 | [70] | Experimental | 52 | 24 | 8 | A = 3, B = 4, C = 5 |
4c | DREAMMCF7 | [70] | Experimental | 47 | 32 | 8 | A = 3, B = 4, C = 5 |
4d | DREAMUACC812 | [70] | Experimental | 52 | 32 | 8 | A = 3, B = 4, C = 5 |
The most relevant factors are the number of observed variables, the number of experiments considered for training, the number of experiments considered for prediction and the different maximum in-degrees tested in each case study.