| Literature DB >> 17540678 |
Jiajing Wang1, Huai Li, Yitan Zhu, Malik Yousef, Michael Nebozhyn, Michael Showe, Louise Showe, Jianhua Xuan, Robert Clarke, Yue Wang.
Abstract
SUMMARY: VISDA (Visual Statistical Data Analyzer) is a caBIG analytical tool for cluster modeling, visualization and discovery that has met silver-level compatibility under the caBIG initiative. Being statistically principled and visually interfaced, VISDA exploits both hierarchical statistics modeling and human gift for pattern recognition to allow a progressive yet interactive discovery of hidden clusters within high dimensional and complex biomedical datasets. The distinctive features of VISDA are particularly useful for users across the cancer research and broader research communities to analyze complex biological data. AVAILABILITY: http://gforge.nci.nih.gov/projects/visda/Entities:
Mesh:
Year: 2007 PMID: 17540678 DOI: 10.1093/bioinformatics/btm290
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937