100 10 1 1 10 k0 100 BMC Genomics 2005, 6:131 http://www.biomedcentral.com/1471-2164/6/131 PFrigouterien i2nteraction network generated using the results of "small-scale studies" only Protein interaction network generated using the results of "small-scale studies" only. Average value of k1 as a func- tion of k0 displayed on a log.-log. scale for the network of non-essential proteins (red) and essential proteins (blue) generated from a dataset including only protein interactions derived from small-scale studies. Both the global and essential networks dis- play similar topological properties with both only exhibiting a very weak negative correlation. into account the connectivity of the proteins within the essential sub-network. By mimicking the degree distribution of nodes within the essential network in the generated random networks, the average number of nodes encompassed within the largest connected component increased from 33% (using a standard randomisation strategy) to 88% over 1000 iterations. Although connec- tivity levels equal to that of the essential sub-network were not observed, levels as high as 92% connectivity were achieved. Discussion In this study, we have shown how the choice of dataset and modelling methodology can profoundly affect the outcome of investigations into the topology of the yeast protein interaction network. We show that, while these variables have little effect on the apparent power-law degree distribution of nodes within the network, they can dramatically alter the correlation between the connectivi- ties of neighbouring nodes. These results raise the ques- tion of what data should be included in these studies and, in the case of protein complex data, which of the two pro- posed modelling methods is the most appropriate for its incorporation? In a recent study, Bader and Hogue [16] showed that pairs identified using the spoke model were more likely to be correct (i.e. in agreement with published literature) than interactions derived using the matrix model. However, Cornell and co-workers [19] showed that there is little difference between the two modelling methods when the annotations of protein pairs found using each model were compared. This indicates that pairs derived using the matrix model are equally as meaningful (in terms of their functional annotation) as those derived using the spoke model, suggesting that either method pro- vides a valid approach to modelling interactions. In fact, if we wish to include the "classical" hand-annotated MIPS complexes within our analyses, the matrix model becomes our only viable option, as it is the only method Page 4 of 8 (page number not for citation purposes)