This article presents a tutorial survey of some of the recent results on intervention in the context of probabilistic gene regulatory networks, which, owing to their original binary formulation and their usual application using binary and ternary gene-expression quantization, are generically called probabilistic Boolean networks (PBNs). These are essentially probabilistic generalizations of the standard Boolean networks introduced by Kauffman that allow the incorporation of uncertainty into the intergene relationships. Given a PBN, the transition from one state to the next takes place in accordance with certain transition probabilities and their dynamics, and hence intervention can be studied in the context of homogeneous Markov chains with finite state spaces
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Datta et al. (2007) studied this question.
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