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

doi:10.1093/bioinformatics/btr052

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^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

33 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 language	English
Article number	btr052
Pages (from-to)	1036-1038
Number of pages	3
Journal	Bioinformatics
Volume	27
Issue number	7
DOIs	https://doi.org/10.1093/bioinformatics/btr052
State	Published - 04 2011
Externally published	Yes

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title = "DDN: A caBIG{\textregistered} analytical tool for differential network analysis",

abstract = "Differential dependency network (DDN) is a caBIG{\textregistered} (cancer Biomedical Informatics Grid) analytical tool for detecting and visualizing statistically significant topological changes in transcriptional networks representing two biological conditions. Developed under caBIG{\textregistered}'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.",

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

year = "2011",

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doi = "10.1093/bioinformatics/btr052",

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volume = "27",

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T2 - A caBIG® analytical tool for differential network analysis

AU - Zhang, Bai

AU - Tian, Ye

AU - Jin, Lu

AU - Li, Huai

AU - Shih, Ie Ming

AU - Madhavan, Subha

AU - Clarke, Robert

AU - Hoffman, Eric P.

AU - Xuan, Jianhua

AU - Hilakivi-Clarke, Leena

AU - Wang, Yue

PY - 2011/4

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AB - 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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DDN: A caBIG® analytical tool for differential network analysis

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