VISDA: an open-source caBIG analytical tool for data clustering and beyond.
CONCLUSIONS
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.


BACKGROUND
http://gforge.nci.nih.gov/projects/visda/
Wang
Jiajing
J
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Li
Huai
H
Zhu
Yitan
Y
Yousef
Malik
M
Nebozhyn
Michael
M
Showe
Michael
M
Showe
Louise
L
Xuan
Jianhua
J
Clarke
Robert
R
Wang
Yue
Y
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D016208:Databases, Factual; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software