Random Research highlight: Constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Every day thousands of proteomics experiments need to be analyzed and compared to these networks. We demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks with or without additional proteomics data. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. Bioinformatics (2011) 27 (3): 405-407. doi: 10.1093/bioinformatics/btq680.