ArticleMethods in molecular biology (Clifton, N.J.)2022
Gene Co-expression Network Analysis.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrative systems biology analysis of barley transcriptome ─ hormonal signaling against biotic stress.PloS one · 2023Pooled it
- Diagnostic Value of Oxidative Stress-Related Features Mined by WGCNA and Machine Learning in Respiratory Syncytial Virus Infection.Advanced biology · 2026Article
- GATSBI: improving context-aware protein embeddings through biologically motivated data splits.Bioinformatics (Oxford, England) · 2026Article
- GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.bioRxiv : the preprint server for biology · 2026Article
- Molecular Signatures of Blood Biomarkers in Depression: Gene Expression Analysis ofDiagnostics (Basel, Switzerland) · 2026Article
- Network-based exploration of 4-(phenylsulfonyl)morpholine molecules for metastatic triple-negative breast cancer suppression.PLoS computational biology · 2026Article
- The genome of the medicinal plant Uncaria rhynchophylla provides new insights into monoterpenoid indole alkaloid metabolism and its molecular regulatory mechanism.Molecular horticulture · 2026Article
- Combining co-expression analysis and machine learning to explore the diagnostic value of complement and coagulation cascade-related genes in asthma and the functional role of SERPINB2.Briefings in functional genomics · 2026Article
- Integrative Machine Learning and Single-Cell RNA Sequencing Reveals Timp1+ Stromal Cells as Key Drivers in Ulcerative Colitis.Journal of inflammation research · 2026Article
- Identification of a Two-Gene Biomarker Correlated with Sensitivity to Combined PARP7 Inhibition and AHR Activation in Cancer Cells.Cancer research communications · 2026Article
- Genetic Insights in Hindbrain Abnormalities Through Network Analysis Expose Key Biological Pathways in Hindbrain Development.Cerebellum (London, England) · 2025Article
- Phylogenetic relationship of WRKY transcription factors inPlant signaling & behavior · 2025Article
- Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.Quantitative biology (Beijing, China) · 2025Review
- Multi-Omics and Experimental Validation Identify GPX7 and Glutathione-Associated Oxidative Stress as Potential Biomarkers in Ischemic Stroke.Antioxidants (Basel, Switzerland) · 2025Article
- Elucidation of the genetic basis of variation in flowering time in Brassica napus via genome-wide association studies and gene coexpression analysis.BMC plant biology · 2025Article
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Identification of phenotypic and transcriptomic signatures underpinning maize crown root systems.Plant phenomics (Washington, D.C.) · 2025Article
- The crucial role of mitochondrial/chloroplast-related genes in viral genome replication and host defense: integrative systems biology analysis in plant-virus interaction.Frontiers in microbiology · 2025Article
- Clinico-demographic and biochemical correlation of inflammatory gene expression in pediatric nephrotic syndrome.Molecular biology reports · 2024Article
- Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum.The plant genome · 2024Article
Corrections and comments
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Abstract
Gene co-expression analysis is a data analysis technique that helps identify groups of genes with similar expression patterns across several different conditions. By means of these techniques, different groups have been able to assign putative metabolic pathways and functions to understudied genes and to identify novel metabolic regulation networks for different metabolites. Some groups have even used network comparative studies to understand the evolution of these networks from green algae to land plants. In this chapter, we will go over the basic definitions required to understand network topology and gene module identification. Additionally, we offer the reader a walk-through a standard analysis pipeline as implemented in the package WGCNA that takes as input raw fastq files and obtains co-expressed gene clusters and representative gene expression patterns from each module for downstream applications.
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Registered trials
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