{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T09:05:22Z","timestamp":1772183122568,"version":"3.50.1"},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Summary: Differential dependency network (DDN) is a caBIG\u00ae (cancer Biomedical Informatics Grid) analytical tool for detecting and visualizing statistically significant topological changes in transcriptional networks representing two biological conditions. Developed under caBIG\u00ae 's In Silico Research Centers of Excellence (ISRCE) Program, DDN enables differential network analysis and provides an alternative way for defining network biomarkers predictive of phenotypes. DDN also serves as a useful systems biology tool for users across biomedical research communities to infer how genetic, epigenetic or environment variables may affect biological networks and clinical phenotypes. Besides the standalone Java application, we have also developed a Cytoscape plug-in, CytoDDN, to integrate network analysis and visualization seamlessly.<\/jats:p><jats:p>Availability: The Java and MATLAB source code can be downloaded at the authors' web site http:\/\/www.cbil.ece.vt.edu\/software.htm<\/jats:p><jats:p>Contact: \u00a0yuewang@vt.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr052","type":"journal-article","created":{"date-parts":[[2011,2,5]],"date-time":"2011-02-05T01:12:51Z","timestamp":1296868371000},"page":"1036-1038","source":"Crossref","is-referenced-by-count":36,"title":["DDN: a caBIG\u00ae analytical tool for differential network analysis"],"prefix":"10.1093","volume":"27","author":[{"given":"Bai","family":"Zhang","sequence":"first","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, 2Bioinformatics Unit, RRB, National Institute on Aging, NIH, Baltimore, MD 21224, 3Departments of Gynecology\/Obstetrics, Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, 4Lombardi Comprehensive Cancer Center and Department of Oncology, Georgetown University, Washington, DC 20057 and 5Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC 20010, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Tian","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, 2Bioinformatics Unit, RRB, National Institute on Aging, NIH, Baltimore, MD 21224, 3Departments of Gynecology\/Obstetrics, Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, 4Lombardi Comprehensive Cancer Center and Department 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