Bioinformatics role of the WGCNA analysis and co-expression network identifies of prognostic marker in lung cancer.

ABSTRACT: Lung cancer is the most talked about cancer in the world. It is also one of the cancers that currently has a high mortality rate. The aim of our research is to find more effective therapeutic targets and prognostic markers for human lung cancer. First, we download gene expression data from the GEO database. We performed weighted co-expression network analysis on the selected genes, we then constructed scale-free networks and topological overlap matrices, and performed correlation modular analysis with the cancer group. We screened the 200 genes with the highest correlation in the cyan module for functional enrichment analysis and protein interaction network construction, found that most of them focused on cell division, tumor necrosis factor-mediated signaling pathways, cellular redox home

SUBMITTER: Chengcheng L 

PROVIDER: S-EPMC9280221 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature