Methodology article
caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data
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* Corresponding author: Yue Wang yuewang@vt.edu
1 Department of Electrical and Computer Engineering, Virginia Polytechnic and State University, Arlington, VA 22203, USA
2 Bioinformatics Unit, RRB, National Institute on Aging, NIH, Baltimore, MD 21224, USA
3 Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
4 Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC 20010, USA
5 Department of Oncology, Physiology & Biophysics and Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, USA
BMC Bioinformatics 2008, 9:383 doi:10.1186/1471-2105-9-383
Published: 18 September 2008Additional 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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