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Table 2 26 genes identified by gene co-expression network with k-core algorithm

From: Genes related to the very early stage of ConA-induced fulminant hepatitis: a gene-chip-based study in a mouse model

Gene symbol Clustering Coefficient Degree k-core
ACSL1 0.418894827 34 11
ALDH8A1 0.489230782 26 11
CAR5A 0.589473665 20 11
CMTM8 0.464615375 26 11
FASTKD1 0.594736814 20 11
FBXO3 0.467980295 29 11
GPD1L 0.637426913 19 11
HLF 0.757352948 17 11
KLB 0.608187139 19 11
MAP2K6 0.70588237 17 11
MPDZ 0.377896607 34 11
MSRB2 0.509803951 18 11
MTAP 0.608333349 16 11
ORMDL1 0.430107534 31 11
PARD3 0.619047642 15 11
PDE7B 0.486166 23 11
POLG2 0.565217376 23 11
SLC29A1 0.393548399 31 11
SOX5 0.492307693 26 11
STARD5 0.666666687 15 11
TERT 0.452631593 20 11
COLEC11 0.494505495 14 10
DPP4 0.495238096 15 10
CDH2 0.561904788 15 9
COLEC12 0.604395628 14 9
FN3K 0.551282048 13 9
  1. Degrees describe the number of single gene that regulates other genes represent the size of the cycle node. The higher the degree, the more central the gene occurs within the network. The clustering coefficient can be used to estimate the complexity of interactions among genes that neighbor the core gene with the exception of core gene participation. The lower the clustering coefficients, the more independent of the core gene are the interactions among genes in the neighborhood of the core gene. A k-core of a gene co-expression network usually contains cohesive groups of genes. The higher the k-core, the more central the genes occurs within the network. In this study, the top k-value is 11, which is considered to have a core status within a large-scale gene network made up of differential genes from profiles No.9 and No. 16.