ArticleBioinformatics (Oxford, England)2022
CBNplot: Bayesian network plots for enrichment analysis.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
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- Uncovering the Key Circuit FOSL2/FOS/EGR3/EGR1, Contributing to the Hyperexcitability of Excitatory Neurons in the Epileptic Temporal Cortex and Hippocampus.International journal of molecular sciences · 2026Article
- Mechanistic insights into SOCS5-related DNA damage and cellular senescence in diabetic retinopathy.Cell death discovery · 2026Article
- BIRC3-CASP8 axis orchestrates the PANoptosis spectrum: taming the inflammatory storm to prevent post-ischemic heart failure.Frontiers in immunology · 2026Article
- Integration of angiogenesis and programmed cell death mechanisms unveils potential diagnostic and therapeutic targets in spinal cord injury.Journal of translational medicine · 2025Article
- Identification of a super enhancer associated gene signature for the prognosis prediction and regulatory mechanism exploration in breast cancer.Scientific reports · 2025Article
- Mendelian Randomization Combined with Bioinformatics Revealed Specific Allergy-Mediated Protective Mechanisms Against Renal Cell Carcinoma.Phenomics (Cham, Switzerland) · 2025Article
- A novel programmed cell death signature predicts clinical outcomes in clear cell renal cell carcinoma and identifies PLK1 as a therapeutic target.Apoptosis : an international journal on programmed cell death · 2025Article
- Differential Expression of Disulfidptosis-Related Genes in Spinal Cord Injury and Their Role in the Immune Microenvironment.Molecular neurobiology · 2025Article
- Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning.Scientific reports · 2025Article
- ACSL5 mediates macrophage infiltration and lipid metabolism in erythrotelangiectasia rosacea via potential pathogenic mechanisms and therapeutic targets.Scientific reports · 2025Article
- Minimum uncertainty as Bayesian network model selection principle.BMC bioinformatics · 2025Article
- Molecular subtyping of renal clear cell carcinoma based on prognostic RASSF family genes and validation of C1QL1 as a key prognostic marker.Scientific reports · 2025Article
- The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers.Journal of translational medicine · 2025Article
- Modulation of brain immune microenvironment and cellular dynamics in systemic inflammation.Theranostics · 2025Article
- Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.Frontiers in immunology · 2025Article
- Augmenting antitumor efficacy of Th17-derived Th1 cells through IFN-γ-induced type I interferon response network via IRF7.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Singular Value Decomposition-Driven Non-negative Matrix Factorization with Application to Identify the Association Patterns of Sarcoma Recurrence.Interdisciplinary sciences, computational life sciences · 2024Article
- Cross-talk between oxidative stress and lipid metabolism regulators reveals molecular clusters and immunological characterization in polycystic ovarian syndrome.Lipids in health and disease · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
summaryWhen investigating gene expression profiles, determining important directed edges between genes can provide valuable insights in addition to identifying differentially expressed genes. In the subsequent functional enrichment analysis (EA), understanding how enriched pathways or genes in the pathway interact with one another can help infer the gene regulatory network (GRN), important for studying the underlying molecular mechanisms. However, packages for easy inference of the GRN based on EA are scarce. Here, we developed an R package, CBNplot, which infers the Bayesian network (BN) from gene expression data, explicitly utilizing EA results obtained from curated biological pathway databases. The core features include convenient wrapping for structure learning, visualization of the BN from EA results, comparison with reference networks, and reflection of gene-related information on the plot. As an example, we demonstrate the analysis of bladder cancer-related datasets using CBNplot, including probabilistic reasoning, which is a unique aspect of BN analysis. We display the transformability of results obtained from one dataset to another, the validity of the analysis as assessed using established knowledge and literature, and the possibility of facilitating knowledge discovery from gene expression datasets. AVAILABILITY AND IMPLEMENTATION: The library, documentation and web server are available at https://github.com/noriakis/CBNplot. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.