GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package, BMC Bioinformatics

Full article: Weighted gene co-expression network analysis (WGCNA) to explore genes responsive to Streptococcus oralis biofilm and immune infiltration analysis in human gingival fibroblasts cells

Weighted gene co‑expression network analysis in identification of key genes and networks for ischemic‑reperfusion remodeling myocardium

Papers and Relevant Publications

Unsupervised Machine Learning Identifies Chromatin Accessibility Regulatory Networks that Define Cell State Transitions in Pluripotency

PDF) GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation

PDF) GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package

Clustering using WGCNA - Bioinformatics Team (BioITeam) at the University of Texas - UT Austin Wikis

Multiscale Embedded Gene Co-expression Network Analysis

GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package, BMC Bioinformatics

Unsupervised Machine Learning Identifies Chromatin Accessibility Regulatory Networks that Define Cell State Transitions in Pluripotency

Transcriptome Analysis and Weighted Gene Co-expression Network Reveal Multitarget-Directed Antibacterial Mechanisms of Benzyl Isothiocyanate against Staphylococcus aureus

Integrative Transcriptomic and Metabolomic Analysis at Organ Scale Reveals Gene Modules Involved in the Responses to Suboptimal

Unsupervised Machine Learning Identifies Chromatin Accessibility Regulatory Networks that Define Cell State Transitions in Pluripotency