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Table 1 Comparison of five network features for the dK distribution models with that of the MIPS protein interaction network, d = 1, 2, 3.

From: Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach

Metric λ 1 λ n-1 d σ d r
MIPS 0.03 1.97 4.42 1.12 -0.14
1k 0.07(0.018) 1.93(0.018) 3.95(0.0117) 0.9045 -0.07(0.0058)
2k 0.06(0.014) 1.94(0.014) 4.04(0.0097) 0.9679 -0.12(0.0035)
3k 0.04(0.014) 1.96(0.014) 4.26(0.0107) 1.0613 -0.14(0.0014)
  1. λ1: average of the smallest eigenvalue of the Laplacian of the graph matrix; λn-1: average of the largest eigenvalue of the Laplacian of the graph matrix; d: average shortest distance between the nodes; σ d : standard deviation of shortest distance between the nodes; r: average assortativity coefficients. The quantity in the brackets indicate the standard deviation of corresponding metric