  We propose a method to identify all the nodes that are relevant to compute
all the conditional probability distributions for a given set of nodes. Our
method is simple, effcient, consistent, and does not require learning a
Bayesian network first. Therefore, our method can be applied to
high-dimensional databases, e.g. gene expression databases.
