Fig. 5: Application to 16 non-linear gene regulatory networks: no noise.
a Feedforward loop (FFL) network models. Across all 16 models (Table 1), F11, F22, and F33 values are fixed at -1 and F12, F13, and F23 values are fixed at 0. F21, F31, and F32 values can be positive or negative depending on the model. The combined effect of x1 and x2 on x3 is described by either an AND gate or an OR gate. There are 16 possible model structures (Table 1). b 100% inhibitory perturbations may not provide accurate classification even without noise. In Model #1, F31 is positive (ground truth) but is estimated as null. c Specific structure of Model #1. d Node activity simulation data for 100% inhibition in Model #1, implying that it is impossible to infer F31 from such data. e Node activity simulation data for 50% inhibition in Model #1, showing potential to infer F31. f Fraction of model parameters correctly classified in all the 16 non-linear models without noise, for 100% inhibition vs 50% inhibition.
