Inferring topology from clustering coefficients in protein-protein interaction networks

Background: Although protein-protein interaction networks determined with high-throughput methods are incomplete, they are commonly used to infer the topology of the complete interactome. These partial networks often show a scale-free behavior with only a few proteins having many and the majority having only a few connections. Recently, the possibility was suggested that this scale-free nature may not actually reflect the topology of the complete interactome but could also be due to the error proneness and incompleteness of large-scale experiments. Results: In this paper, we investigate the effect of limited sampling on average clustering coefficients and how this can help to more confidently exclude possible topology models for the complete interactome. Both analytical and simulation results for different network topologies indicate that partial sampling alone lowers the clustering coefficient of all networks tremendously. Furthermore, we extend the original sampling model by also in...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Caroline C. Friedel, Ralf Zimmer
• Keywords: BMCBI 2006, Clustering Coefficients, Complete Interactome, Topology