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Effects of false positive rates in prior knowledge on inference of the differential network. (a) Precision of differential network inference. (b) Recall of differential network inference. The experiments show that true knowledge improves both precision and recall of differential network inference. The maximum degradation of inference results is bounded when the prior knowledge is imperfect.
