100 10 1 1 10 100 1000 k0 BMC Genomics 2005, 6:131 http://www.biomedcentral.com/1471-2164/6/131 FDiIgPu-braese1d protein interaction network using the spoke model DIP-based protein interaction network using the spoke model. Mean connectivity of neighbouring nodes (<k1>) as a function of the connectivity of the central node (k0) displayed on a log.-log. scale for the "global" network (blue) and "essential" sub-network (red), generated from interactions extracted from the yeast subset of the DIP database. Note the difference in topology between the two networks. between the topologies of the global and essential gene networks are no longer evident, with both having similar slopes (αk0:k1 -0.10 global v -0.09 essential) and correla- tion coefficients (rk0:k1 -0.39 global v -0.34 essential) between log(<k1>) and log(k0). This result suggests that the significant negative correlation previously observed within the global network results mainly from data gener- ated using high-throughput methods. Variation in modelling methodology Following the dataset-dependent observations described above, the impact of applying different modelling meth- odologies to experimental data on protein complexes was assessed. The application of the matrix model to the pro- tein complex data contained within the cohort used in Figure 1, and reanalysis of the resulting network, causes a dramatic shift in the topology of the network. Again, the power-law degree-distribution for nodes within the net- work is found. However, the previously observed negative correlation between log(<k1>) and log(k0) changes to a positive correlation for both the global and essential sub- networks, with both networks showing similar topologi- cal characteristics (Figure 3) (for K0 ≤ 195, global network rk0:k1 = 0.68 αk0:k1 = 0.17, essential sub-network; rk0:k1 = 0.88, αk0:k1 = 0.27). Randomisation strategy A second prominent finding of earlier work investigating the yeast protein interaction network is that the essential sub-network is very highly connected, with ≈ 97% of all proteins within it being connected in a single giant com- ponent [15]. The significance of this result was previously highlighted using a standard randomisation strategy, in which a number of nodes equivalent to that in the essen- tial network were randomly selected from the global net- work and the connectivity of the resultant sub-network determined. To assess the validity of this finding, a "biased" randomisation strategy was employed that took Page 3 of 8 (page number not for citation purposes)