An outline of the workflow in network inference and control in the PBN framework. Microarray data, either from steady-state or time-course measurements, are typically binarised or discretised into discrete values. A heuristic approach, such as using genetic algorithms, is generally applied to identify constituent Boolean networks of the inferred PBN. Regularisation methods can be further applied to improve the accuracy of the inference with use of prior information on the network structure or dynamical rules. A number of well-established methods are subsequently applied to determine the predictor probability of each constituent Boolean network, thus the PBN is inferred. The inferred PBN can subsequently be perturbed with the methods on structural intervention or external control. The goal of network control is to increase the probability of reaching desirable states in the corresponding PBN.