Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

Table 3 Network parameters of the functional similarity networks.

Parameter Type	Organism	PPI ^a)	BP ^b)	CC	MF	*funSim*
Degree exponent (γ)	E. coli	1.38	0.74 0.99 1.14	-0.05 0.37 0.24	0.52 0.85 1.33	0.93 1.37 1.16
	S. cerevisiae	1.80	0.90 1.22 1.23	0.13 0.83 0.80	0.51 0.96 1.15	1.32 1.31 1.13
	P. falciparum	1.60	0.35 1.02 0.89	0.09 0.73 0.72	0.25 0.21 0.93	0.94 1.27 1.22
Cluster coefficient <C(k)>	E. coli	0.08	0.74 0.75 0.77	0.67 0.85 0.79	0.82 0.74 0.69	0.65 0.49 0.45
	S. cerevisiae	0.10	0.50 0.63 0.58	0.75 0.77 0.77	0.72 0.72 0.62	0.46 0.46 0.50
	P. falciparum	0.01	0.70 0.74 0.60	0.75 0.86 0.77	0.88 0.82 0.75	0.44 0.64 0.62
Clustering degree exponent (β)^c)	E. coli	0.75	0.31 -0.08 0.06	0.01 -0.19 -0.22	0.40 0.40 0.55	0.51 1.29 0.52
	S. cerevisiae	1.26	0.45 0.11 0.38	0.08 -0.05 -0.02	0.13 0.40 0.50	2.12 1.39 0.67
	P. falciparum	0.20	-0.20 0.51 0.42	0.26 0.57 0.39	-0.15 0.34 0.10	0.80 1.39 1.15

a) The PPI networks shown in Figure 1.
b) The degree distributions of the functional similarity networks (Fig. 3) are fit to the power-law distribution, P(k) ~ k^-γand the value of γ (the degree component) is computed. The values for the networks with the similarity score threshold value of 0.80 (top), 0.95 (middle, underlined), and 0.99 (bottom) are shown. Only edges with the threshold value or higher are considered.
c) The average clustering coefficient C(k) relative to the degree k is fit to the clustering-degree function, C(k) ~k-^β. For the PPI, the data with k ≥ 10, while data with k ≥ 100, k ≥ 30, and k ≥ 10 are used for the functional similarity networks with the similarity score threshold value of 0.80, 0.95, and 0.99.

ISSN: 1471-2105