Computational Bioinformatics and Bioimaging Laboratory, Virginia Tech.

Reconstructing Regulatory Networks by Probabilistic Network Component Analysis (pNCA)

Supplementary information on pNCA: pNCA Manual and pNCA Package

The CAM Software for Nonnegative Blind Source Separation in R-Java

Supplementary information on CAM R-Java: CAM R-Java Manual and CAM R-Java Package

A bagging Markov random field (BMRF) approach for PPI subnetwork identification

Supplementary information on BMRF: BMRF Manual and BMRF Package

Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic

Supplementary information - a Gibbs sampler on outlier sum statistic (GibbsOS): GibbsOS Manual and GibbsOS Package (Version 3)

Significant Aberrations in Cancer (SAIC)

Software Information on SAIC: SAIC Manual and SAIC Package

Bayesian Analysis of Copy Number Mixtures (BACOM)

CAM-CM Software for Application Note

Convex Analysis of Mixtures and Compartment Modeling (CAM-CM)

caBIG PUGSVM

CNSuite: A caBIG analytical tool for copy number analysis

CNSuite (Copy Number Suite) is a caBIGTM (cancer Biomedical Informatics Grid) analytical tool for gene copy number change analysis. CNSuite consists of a Fused Margin Regression (FMR) method for detecting copy number changes in a single signal profile and consensus copy number changes in population data, and two feature indexing methods for analyzing chromosomal instabilities (CIN). CNSuite is applicable to analyzing germline copy number variations (CNV) in the study of population genetics and somatic copy number alterations (CNA) in tumor genomics.

Supplementary Information: free download CNSuite software - CNSuite Software

caBIG VIsual and Statistical Data Analyzer (VISDA)

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.

Multi-level Support Vector Regression (ml-SVR) Analysis to Identify Condition-Specific Regulatory Networks

Supplementary Information: free download ml-SVR software - ml-SVR Package

Motif-guided Sparse Decomposition (mSD) of Gene Expression Data for Regulatory Module Identification

Supplementary Information: free download mSD software - mSD 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, PUG-OVRSVM Package Part 3, and PUGSVM-DEPLOYMENT-WINDOWS.rar, and caBIG PUG Package

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 (COCA)

Supplementary Information on Coordinative Component Analysis (COCA): COCA Manual and COCA Package

Differential Dependence Networks (DDN and kDDN)

Supplementary Information on Differential Dependence Networks (DDN): kDDN_Update, DDN_Manual, DDN Package, and caBIG 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 SNP Simulator

Tissue Heterogeneity Correction (THC)

BSS-THC Software (supported by the NIH under Grants EB000830, CA109872): BSS Demo, BSS Demo Readme, and A Tutorial on BSS-1

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)

Last Updated: 02/16/2009. Suggestions/Comments - Webmaster


	Computational Bioinformatics and Bioimaging Laboratory (CBIL)

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