title: VISDA: an open-source caBIG analytical tool for data clustering and beyond.
abstract: 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/
authors.affiliation: Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
authors.forename: Jiajing
authors.initials: J
authors.lastname: Wang
authors.forename: Huai
authors.initials: H
authors.lastname: Li
authors.forename: Yitan
authors.initials: Y
authors.lastname: Zhu
authors.forename: Malik
authors.initials: M
authors.lastname: Yousef
authors.forename: Michael
authors.initials: M
authors.lastname: Nebozhyn
authors.forename: Michael
authors.initials: M
authors.lastname: Showe
authors.forename: Louise
authors.initials: L
authors.lastname: Showe
authors.forename: Jianhua
authors.initials: J
authors.lastname: Xuan
authors.forename: Robert
authors.initials: R
authors.lastname: Clarke
authors.forename: Yue
authors.initials: Y
authors.lastname: Wang
mesh_terms: 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