VISDA (VIsual Statistical Data Analyzer) is a caBIG analytical tool for cluster modeling, visualization, and discovery. Being statistically-principled and visually-insightful, VISDA exploits human gift for pattern recognition and allows users to discover hidden clustered data structure within high dimensional and complex biomedical data sets. The unique features of VISDA include its hybrid algorithm, robust performance, and "tree of phenotype". With global and local biomarker identification and prediction functionalities, VISDA allows users across the cancer research community to analyze their genomic/proteomic data to define new cancer subtypes based on the gene expression patterns, construct hierarchical trees of multiclass cancer phenotypic composites, or to discover the correlation between cancer statistics and risk factors.
Motif-guided Sparse Decomposition (mSD) of Gene Expression Data for Regulatory Module Identification
Supplementary Information: free download mSD software - mSD Package
Multi-level Support Vector Regression (ml-SVR) Analysis to Identify Condition-Specific Regulatory Networks
Supplementary Information: free download ml-SVR software - ml-SVR Package
Phenotype Up-regulated Gene based One Versus Rest Support Vector Machine (PUG-OVRSVM) for Multicategory Molecular Classification
Supplementary Information: free download PUG-OVRSVM software and test datasets PUG-OVRSVM Package Part 1 and
PUG-OVRSVM Package Part 2 and PUG-OVRSVM Package Part 3
Learning Maximum Entropy Probability
Models for Characterizing Multilocus Genomic Interactions
Supplementary Information: free download MECPM-SNP software and test datasets MECPM-SNP Package
Coordinative Component Analysis (CCA)
Supplementary Information on Coordinative Component Analysis (CCA): CCA Manual and
CCA Package
Differential Dependence Networks (DDN)
Supplementary Information on Differential Dependence Networks (DDN): DDN_Manual and
DDN Package
VIsual and Statistical Data Analyzer (VISDA)
Supplementary Information #1 on caBIG VISDA: VISDA Installation Guide
Supplementary Information #2 on caBIG VISDA: VISDA Package
SNP Simulation
Supplementary Information on SNP Simulation: SNP Simulation
Tissue Heterogeneity Correction (THC)
PICA-ISG-THC Software (supported by the NIH under Grants EB000830, CA109872): PICA Demo,
PICA Demo Readme, and
A Tutorial on ISG-PICA
Cross-Phenotype Normalization (CPN)
ISN-INR-CPN Software (supported by the NIH under Grants EB000830, CA109872): CPN Tutorial, and
dchipCPN Package
Optimized Multilayer Perceptrons (oMLP)
Supplementary Information on oMLP (Bioinformatics-2005-1602): Appendices of oMLP (Bioinformatics), and
Appendix A1 of oMLP (Bioinformatics)
Copyright
©2004, Computational Bioinformatics and Bioimaging Laboratory
(CBIL), Advanced Research Institute, Virginia Tech.
Last
Updated: 02/16/2009. Suggestions/Comments
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