  One of the most important concepts in biological network analysis is that of
network motifs, which are patterns of interconnections that occur in a given
network at a frequency higher than expected in a random network. In this work
we are interested in searching and inferring network motifs in a class of
biological networks that can be represented by vertex-colored graphs. We show
the computational complexity for many problems related to colorful topological
motifs and present efficient algorithms for special cases. We also present a
probabilistic strategy to detect highly frequent motifs in vertex-colored
graphs. Experiments on real data sets show that our algorithms are very
competitive both in efficiency and in quality of the solutions.
