… GO [11] or co-expression databases; and disease-disease similarity information from HPO
or MimMiner [24]. We survey the network-based methods in three categories in this section. …

… Our first CoDiNA network represents the comparison of the full gene co-expression network
of … Gene co-expression analysis for functional classification and gene-disease predictions. …

… Step 3 further selects a subset of genes from the candidate pool whose co-expression
patterns are best preserved for building prediction models. Gene co-expression patterns …

… for the construction of weighted gene co-expression networks. Rather than focusing only
on differential gene expression, WGCNA uses information from the genome to identify a set of …

… Through KEGG and GO enrichment analysis and differential co-expression analysis, we
investigated the biological functions of the 674 biomarkers and proposed possible molecular …

… genetic foundations of these discrepancies through the utilization of Weighted Gene Co-expression
Network Analysis (… from applying the XGBoost model predictions based on the blue …

… Weighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression
modules and networks based on the Chinese Glioma Genome Atlas (CGGA) …

… categories do not depend of the cut-off value. Here, we have provided a methodology to
discover functional characteristics of gene-co-expression … aware that gene co-expression may …

… Gene co-expression networks based on sequencing data are beneficial in establishing a
comprehensive view of gene co-expression … to construct a gene co-expression network via …

… gene co-expression network analysis to examine the modules concerning infiltrated M2-TAMs.
Gene Ontology analysis and pathway enrichment analysis … genes together for predicting …