Abstract. We study local pattern mining in the context of probabilistic relational databases, developing algorithms for probabilistic variants of both frequent and correlated pattern mining that use principles of statis-tical relational learning. As probabilistic selection criteria, we introduce both a likelihood function and a probabilistic frequency. We report on experiments on a challenging biological network mining task. 1