Figure 4From: The extended TILAR approach: a novel tool for dynamic modeling of the transcription factor network regulating the adaption to in vitro cultivation of murine hepatocytesResults of the parameter study optimizing the parameter values for the input weight and the auto-regulation weight. Outlined is the ratio of the number of included prior-knowledge relations to the total number of inferred relations excluding the input-to-gene relations (precision). Based on this result and whether or not numerical simulation of the inferred network led to dynamics comparable to the observed ones, the auto-regulation weight was set to 0.75 while the input weight was set to 0.5.Back to article page