Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality.

We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g.

Dynamic spatiotemporal brain analyses using high performance electrical neuroimaging: theoretical framework and validation.

Background: Since Berger's first EEG recordings in 1929, several techniques, initially developed for investigating periodic processes, have been applied to study non-periodic event-related brain state dynamics.

New Method: We provide a theoretical comparison of the two approaches and present a new suite of data-driven analytic tools for the specific identification of the brain microstates in high-density event-related brain potentials (ERPs). This suite includes four different analytic methods.

GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects.

Background: Dominance effect may play an important role in genetic variation of complex traits. Full featured and easy-to-use computing tools for genomic prediction and variance component estimation of additive and dominance effects using genome-wide single nucleotide polymorphism (SNP) markers are necessary to understand dominance contribution to a complex trait and to utilize dominance for selecting individuals with favorable genetic potential.

Results: The GVCBLUP package is a shared memory parallel computing tool for genomic prediction and variance component estimation of additive and dominance effects using genome-wide SNP markers.