January 15, 2010
Journal Article

VIBE 2.0: Visual Integration for Bayesian Evaluation

Abstract

Data fusion methods are powerful tools for evaluating experiments designed to discover measurable features of directly unobservable systems. We describe an interactive software platform, Visual Integration for Bayesian Evaluation (VIBE), which ingests Bayesian posterior probability matrices, performs data fusion, and allows the user to interactively evaluate the classification power of fusing various combinations of data sources, such as transcriptomic, proteomics, metabolomics, biochemistry and function.

Revised: November 12, 2010 | Published: January 15, 2010

Citation

Beagley N., K.G. Stratton, and B.M. Webb-Robertson. 2010. VIBE 2.0: Visual Integration for Bayesian Evaluation. Bioinformatics 26, no. 2:280-282. PNNL-SA-66347.