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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