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Network analytic method designed for the analysis of static networks promise to identify significant relational patterns that correlate with important structures in the complex system the network is derived from. In this mini review, three groups of network analytic methods are discussed: centrality indices, network motifs, and clustering algorithms. We show that so far these methods have mainly been used in a descriptive way, but that they show promising possibilities to be used for prediction and classification. We thus conclude the article with a discussion of how benchmark sets and evaluation criteria could look like to realize this promise.

Good versus optimal: Why network analytic methods need more systematic evaluation