VISDA：一个用于数据聚类及其他功能的开源caBIG分析工具。
VISDA: an open-source caBIG analytical tool for data clustering and beyond.
作者信息
Wang Jiajing, Li Huai, Zhu Yitan, Yousef Malik, Nebozhyn Michael, Showe Michael, Showe Louise, Xuan Jianhua, Clarke Robert, Wang Yue
机构信息
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
出版信息
Bioinformatics. 2007 Aug 1;23(15):2024-7. doi: 10.1093/bioinformatics/btm290. Epub 2007 May 31.
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
摘要
VISDA（可视化统计数据分析器）是一种用于聚类建模、可视化和发现的caBIG分析工具，已在caBIG计划下达到银级兼容性。VISDA基于统计原则并具有可视化界面，它利用层次统计建模和人类的模式识别天赋，以便在高维和复杂的生物医学数据集中逐步且交互式地发现隐藏的聚类。VISDA的独特功能对于癌症研究及更广泛研究领域的用户分析复杂生物数据特别有用。
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