DDN: A caBIG® analytical tool for differential network analysis

Bai Zhang, Ye Tian, Lu Jin, Huai Li, Ie Ming Shih, Subha Madhavan, Robert Clarke, Eric P. Hoffman, Jianhua Xuan, Leena Hilakivi-Clarke, Yue Wang

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Differential dependency network (DDN) is a caBIG® (cancer Biomedical Informatics Grid) analytical tool for detecting and visualizing statistically significant topological changes in transcriptional networks representing two biological conditions. Developed under caBIG®'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.

Original languageEnglish (US)
Article numberbtr052
Pages (from-to)1036-1038
Number of pages3
JournalBioinformatics
Volume27
Issue number7
DOIs
StatePublished - Apr 2011
Externally publishedYes

Bibliographical note

Funding Information:
Funding: National Institutes of Health, under Contract No. HHSN261200800001E and Grants CA109872, CA149147, NS029525, GM085665 (in parts); Intramural Research Program of the National Institutes of Health, National Institute on Aging (in parts).

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