VISDA: an open-source caBIG™ analytical tool for data clustering and beyond
| Autor: | Michael Nebozhyn, Malik Yousef, Yitan Zhu, Jiajing Wang, Jianhua Xuan, Louise C. Showe, Yue Joseph Wang, Robert Clarke, Huai Li, Michael Showe |
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| Rok vydání: | 2007 |
| Předmět: |
Statistics and Probability
Biological data Databases Factual Computer science Gene Expression Profiling Information Storage and Retrieval Biochemistry Data science Pattern Recognition Automated Computer Science Applications Visualization Computational Mathematics Open source Computational Theory and Mathematics Artificial Intelligence Cluster Analysis Cluster analysis Molecular Biology Algorithms Software Oligonucleotide Array Sequence Analysis |
| Zdroj: | Bioinformatics. 23:2024-2027 |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | 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/Contact: yuewang@vt.eduSupplementary information: Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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