We propose an algorithm, called BI-GRAPPIN, to search for similarities across PPI networks. The technique core consists in computing a maximum weight matching of bipartite graphs to compare the neighborhoods of pairs of proteins in different PPI networks. The idea is that proteins belonging to different networks should be matched look- ing not only at their own sequence similarity, but also at the similarity of proteins they "strongly" interact with, ei- ther directly or indirectly. We implemented the method and tested it on both real and synthetic data, showing its effec- tiveness in solving ambiguous situations and in individuat- ing functionally related proteins. Differently from previous work, the presented algorithm allows to take into account both quantitative and reliability information possibly avail- able about interactions.