{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T13:13:49Z","timestamp":1782738829303,"version":"3.54.5"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T00:00:00Z","timestamp":1648166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JSPS KAKENHI Grant-in-Aid for Early-Career Scientists","award":["19K18321"],"award-info":[{"award-number":["19K18321"]}]},{"name":"JST COI","award":["JPMJCE1302"],"award-info":[{"award-number":["JPMJCE1302"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>When 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The library, documentation and web server are available at https:\/\/github.com\/noriakis\/CBNplot.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac175","type":"journal-article","created":{"date-parts":[[2022,3,24]],"date-time":"2022-03-24T21:52:41Z","timestamp":1648158761000},"page":"2959-2960","source":"Crossref","is-referenced-by-count":51,"title":["<i>CBNplot<\/i>: Bayesian network plots for enrichment analysis"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7721-9359","authenticated-orcid":false,"given":"Noriaki","family":"Sato","sequence":"first","affiliation":[{"name":"Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshinori","family":"Tamada","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan"},{"name":"Innovation Center for Health Promotion, Hirosaki University, Aomori 036-8562, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6485-8781","authenticated-orcid":false,"given":"Guangchuang","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasushi","family":"Okuno","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan"},{"name":"RIKEN Advanced Institute for Computational Sciences, Hyogo 650-0047, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,3,25]]},"reference":[{"key":"2023020109063938800_btac175-B1","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1038\/ng.2764","article-title":"The Cancer Genome Atlas Pan-Cancer analysis project","volume":"45","year":"2013","journal-title":"Nat. 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