In machine learning, the Markov blanket for a node in a Bayes net consists of the node's parents, its children, and its children's parents. A node is conditionally independent of the entire network, given its Markov blanket.

The values of the parents and children of a node evidently give information about that node. However, its children's parents also have to be included, because they can be used to explain away the node in question.