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Accurate inference of biological systems, such as gene regulatory networks and microbial communities, is a key to a deep understanding of their underlying mechanisms. Despite several advances in the inference of regulatory networks in recent years, the existing techniques cannot incorporate expert knowledge into the inference process. Expert knowledge contains valuable biological information and is often reflected in available biological data, such as interventions made by biologists for treating diseases. Given the complexity of regulatory networks and the limitation of biological data, ignoring expert knowledge can lead to inaccuracy in the inference process. This letter models the regulatory networks using Boolean network with perturbation. We develop an expert-enabled inference method for inferring the unknown parameters of the network model using expert-acquired data. Given the availability of …