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Updated: Sep 23, 2025

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CBNplot: Bayesian network plots for enrichment analysis.

Noriaki Sato1, Yoshinori Tamada1,2, Guangchuang Yu3

  • 1Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.

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|May 13, 2022
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Summary
This summary is machine-generated.

This study introduces CBNplot, an R package for inferring gene regulatory networks (GRNs) using Bayesian networks (BNs) and functional enrichment analysis (EA). It facilitates understanding gene interactions and molecular mechanisms from gene expression data.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Gene expression profiling is crucial for understanding molecular mechanisms.
  • Inferring gene regulatory networks (GRNs) from gene expression data aids in studying these mechanisms.
  • Functional enrichment analysis (EA) can provide pathway insights, but tools for GRN inference based on EA are limited.

Purpose of the Study:

  • To develop an R package, CBNplot, for easy inference of Bayesian networks (BNs) from gene expression data.
  • To integrate functional enrichment analysis (EA) results into GRN inference.
  • To provide tools for visualization, comparison, and knowledge discovery from gene expression data.

Main Methods:

  • Development of the R package CBNplot.
  • Utilizing gene expression data and results from functional enrichment analysis (EA).
  • Implementing structure learning for Bayesian networks (BNs).
  • Incorporating visualization of BNs, comparison with reference networks, and probabilistic reasoning.

Main Results:

  • CBNplot successfully infers Bayesian networks (BNs) from gene expression data by utilizing functional enrichment analysis (EA) results.
  • The package offers features for BN structure learning, visualization, and comparison with reference networks.
  • Demonstrated application on bladder cancer datasets showed the utility of probabilistic reasoning and the transformability of results across datasets.

Conclusions:

  • CBNplot provides a valuable tool for inferring gene regulatory networks (GRNs) by integrating gene expression data with functional enrichment analysis (EA).
  • The package facilitates the visualization and analysis of complex gene interactions, aiding in the discovery of molecular mechanisms.
  • CBNplot enhances knowledge discovery from gene expression datasets through its unique Bayesian network approach.