{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:39:00Z","timestamp":1740184740990,"version":"3.37.3"},"reference-count":9,"publisher":"Oxford University Press (OUP)","issue":"23","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["1R01MH105561-02","U19 AI090023"],"award-info":[{"award-number":["1R01MH105561-02","U19 AI090023"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,12,1]]},"abstract":"<jats:p>Motivation: Network marker selection on genome-scale networks plays an important role in the understanding of biological mechanisms and disease pathologies. Recently, a Bayesian nonparametric mixture model has been developed and successfully applied for selecting genes and gene sub-networks. Hence, extending this method to a unified approach for network-based feature selection on general large-scale networks and creating an easy-to-use software package is on demand.<\/jats:p><jats:p>Results: We extended the method and developed an R package, the Bayesian network feature finder (BANFF), providing a package of posterior inference, model comparison and graphical illustration of model fitting. The model was extended to a more general form, and a parallel computing algorithm for the Markov chain Monte Carlo -based posterior inference and an expectation maximization-based algorithm for posterior approximation were added. Based on simulation studies, we demonstrate the use of BANFF on analyzing gene expression on a protein\u2013protein interaction network.<\/jats:p><jats:p>Availability: \u00a0https:\/\/cran.r-project.org\/web\/packages\/BANFF\/index.html<\/jats:p><jats:p>Contact: \u00a0jiankang@umich.edu, tianwei.yu@emory.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw522","type":"journal-article","created":{"date-parts":[[2016,8,9]],"date-time":"2016-08-09T01:43:59Z","timestamp":1470707039000},"page":"3685-3687","source":"Crossref","is-referenced-by-count":13,"title":["Bayesian network feature finder (BANFF): an R package for gene network feature selection"],"prefix":"10.1093","volume":"32","author":[{"given":"Zhou","family":"Lan","sequence":"first","affiliation":[{"name":"1Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA"}]},{"given":"Yize","family":"Zhao","sequence":"additional","affiliation":[{"name":"2Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY 10065, USA"}]},{"given":"Jian","family":"Kang","sequence":"additional","affiliation":[{"name":"3Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA"}]},{"given":"Tianwei","family":"Yu","sequence":"additional","affiliation":[{"name":"4Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA"}]}],"member":"286","published-online":{"date-parts":[[2016,8,8]]},"reference":[{"key":"2023020114091155400_btw522-B1","doi-asserted-by":"crossref","DOI":"10.1093\/database\/bau126","article-title":"Comparison of human cell signaling pathway databases\u2013evolution, drawbacks and challenges","volume":"2015","author":"Chowdhury","year":"2015","journal-title":"Database (Oxford)"},{"key":"2023020114091155400_btw522-B2","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1073\/pnas.0610772104","article-title":"Global reconstruction of the human metabolic network based on genomic and bibliomic data","volume":"104","author":"Duarte","year":"2007","journal-title":"Proc. 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