Table 2 Centrality Analysis Gene Results.

From: Conserved Transcriptional Signatures in Human and Murine Diabetic Peripheral Neuropathy

Symbol

Description

Degree (p-value)

Closeness (p-value)

Betweenness (p-value)

Eigenvector (p-value)

PIK3CA

phosphoinositide-3-kinase, catalytic, alpha polypeptide

406 (p = 1.8E−08)

0.00081 (p = 6.4E−01)

43246.5 (p = 0.0E + 00)

0.16 (p = 2.9E−03)

MAPK8

mitogen-activated protein kinase 8

372 (p = 3.8E−07)

0.00078 (p = 6.6E−01)

30937.8 (p = 0.0E + 00)

0.15 (p = 6.3E−03)

CD44

CD44 molecule (Indian blood group)

349 (p = 1.3E−08)

0.00075 (p = 6.6E−01)

32129.4 (p = 0.0E + 00)

0.13 (p = 7.3E−03)

MAPK1

mitogen-activated protein kinase 1

280 (p = 3.5E−03)

0.00074 (p = 6.5E−01)

19719.2 (p = 1.7E−03)

0.13 (p = 3.9E−02)

CREB1

cAMP responsive element binding protein 1

283 (p = 1.2E−08)

0.00073 (p = 6.4E−01)

15524.7 (p = 0.0E + 00)

0.12 (p = 3.0E−03)

LEP

leptin

301 (p = 8.7E−10)

0.00072 (p = 6.6E−01)

22639.7 (p = 0.0E + 00)

0.12 (p = 5.6E−03)

CCL2

chemokine (C-C motif) ligand 2

276 (p = 3.3E−03)

0.00071 (p = 6.9E−01)

13595.3 (p = 4.5E−03)

0.12 (p = 1.0E−01)

JUN

jun proto-oncogene

232 (p = 5.9E−03)

0.00071 (p = 6.7E−01)

11905.8 (p = 1.2E−02)

0.12 (p = 4.3E−02)

ESR1

estrogen receptor 1

269 (p = 4.7E−09)

0.00071 (p = 6.6E−01)

17433.2 (p = 0.0E + 00)

0.11 (p = 5.8E−03)

FOS

FBJ murine osteosarcoma viral oncogene homolog

229 (p = 3.1E−03)

0.00070 (p = 6.4E−01)

21885.2 (p = 2.5E−07)

0.10 (p = 7.4E−02)

CD36

CD36 molecule (thrombospondin receptor)

247 (p = 5.0E−07)

0.00070 (p = 6.5E−01)

11865.1 (p = 6.5E−13)

0.11 (p = 7.2E−03)

IL1B

interleukin 1, beta

224 (p = 6.5E−03)

0.00070 (p = 6.6E−01)

12492.5 (p = 3.4E−03)

0.09 (p = 1.6E−02)

HGF

hepatocyte growth factor (hepapoietin A; scatter factor)

213 (p = 9.4E−06)

0.00069 (p = 6.6E−01)

8254.8 (p = 2.6E−07)

0.12 (p = 4.6E−03)

  1. Centrality analysis was conducted using the Cytoscape plug-in CentiScaPe and four centrality metrics (degree, eigenvector, closeness, and betweenness) to identify the most important nodes (i.e., genes) in the merged transcriptional network. The top 10 ranked genes in each perspective centrality metric is included in the table and indicate the most influential genes within the network. The centrality scores of each node were compared against the background distribution of centrality scores that were obtained from randomly generated 1,000 random merged networks. P-values were calculated using z-test to examine the significant difference between the real and random networks.