caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

doi:10.1186/1471-2105-9-383

BMC Bioinformatics

Volume 9

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Methodology article

caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Yitan Zhu¹ , Huai Li¹^,2 , David J Miller³ , Zuyi Wang¹^,4 , Jianhua Xuan¹ , Robert Clarke⁵ , Eric P Hoffman⁴ and Yue Wang¹

¹Department of Electrical and Computer Engineering, Virginia Polytechnic and State University, Arlington, VA 22203, USA

²Bioinformatics Unit, RRB, National Institute on Aging, NIH, Baltimore, MD 21224, USA

³Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA

⁴Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC 20010, USA

⁵Department of Oncology, Physiology & Biophysics and Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, USA

author email corresponding author email

BMC Bioinformatics 2008, 9:383doi:10.1186/1471-2105-9-383


Published:	18 September 2008

Additional files

Additional file 1:

caBIG™ VISDA: modeling, visualization, and discovery for cluster analysis of genomic data (supplement). The supplement includes derivations and details of the algorithm, more discussions, and introduction of the datasets used in the experiments.

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