Bioinformatics Analysis to Screen Key Targets of Curcumin against Colorectal Cancer and the Correlation with Tumor-Infiltrating Immune Cells

Table 2

Topological parameters of the targets.

Targets	Degree	Subgraph	Betweenness	Closeness
AKT1	18	1576.9823	142.27713	0.78125
EGFR	15	1044.5238	123.55815	0.714286
STAT3	14	1046.328	76.63744	0.657895
EP300	12	1024.9966	26.278643	0.625
CDK4	10	789.8613	11.725108	0.595238
MMP9	10	728.5876	40.98225	0.609756
CHEK1	10	700.0684	27.078138	0.581395
GSK3B	9	602.72296	11.776262	0.568182
AURKA	9	560.9203	23.439177	0.555556
RPS6KB1	7	513.06287	1.7409091	0.555556
TOP2A	7	294.21695	9.762843	0.531915
EPHA2	7	255.23312	55.70498	0.555556
NFE2L2	5	301.88513	0.33333334	0.510204
TOP1	5	241.85707	0.5833333	0.510204
TLR9	5	241.24434	1.7222222	0.520833
HDAC4	5	220.83974	3.2777777	0.510204
RAF1	4	152.114	1.0666667	0.5
IKBKB	4	145.47293	1.7599567	0.5
EPHA3	4	43.854324	7.5857143	0.438597
EPHB2	4	37.902145	4.2099566	0.416667
BRAF	3	85.04361	0	0.480769
HDAC7	3	74.83233	0.5	0.471698
ADRBK1	3	63.870117	48	0.490196
MELK	3	56.340717	0	0.396825
EPHA7	3	14.385622	0	0.373134
MAOA	1	2.3126676	0	0.333333