DDN: a caBIG® analytical tool for differential network analysis | Zendy

Bai Zhang | Zendy; Ye Tian | Zendy; Lü Jin | Zendy; Huai Li | Zendy; IeMing Shih | Zendy; Subha Madhavan | Zendy; Robert Clarke | Zendy; Eric P. Hoffman | Zendy; Jianhua Xuan | Zendy; Leena HilakiviClarke | Zendy; Yue Wang | Zendy

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DDN: a caBIG® analytical tool for differential network analysis

Author(s) -

Bai Zhang,

Ye Tian,

Lü Jin,

Huai Li,

IeMing Shih,

Subha Madhavan,

Robert Clarke,

Eric P. Hoffman,

Jianhua Xuan,

Leena HilakiviClarke,

Yue Wang

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr052

Subject(s) - computer science , java , source code , visualization , biological network , data mining , network analysis , plug in , software , gene regulatory network , bioinformatics , biology , programming language , genetics , physics , quantum mechanics , gene expression , gene

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.

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