Detecting the tipping points in a three-state model of complex diseases by temporal differential networks

Table 1 Graph-related information of twelve networks with most significant I-scores

Network	Centre gene	Number of nodes	Turnover edges	Ratio of turnover edges	Turnover nodes	Ratio of turnover nodes	Significance
1	Hsp90ab1	74	26	0.36	45	0.61	2.0E−6
2	Slc2a1	40	13	0.33	23	0.58	7.0E−6
3	Hspa1b	57	25	0.45	35	0.61	2.0E−5
4	Thbs1	26	15	0.60	16	0.62	3.8E−4
5	Ptgs2	55	26	0.48	35	0.64	1.9E−3
6	Hspa1a	55	32	0.59	30	0.55	7.3E−4
7	Fos	73	29	0.40	47	0.64	5.1E−3
8	Cdkn1a	46	15	0.33	34	0.74	3.5E−5
9	Plaur	28	11	0.41	19	0.68	1.4E−5
10	Gadd45g	15	5	0.36	12	0.80	1.6E−5
11	Gclc	29	11	0.39	22	0.76	0
12	Dusp1	46	15	0.33	32	0.70	1.9E−3

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