B0706
Title: A Bayesian approach for array-variate biological networks
Authors: Yang Ni - Rice University (United States)
Veerabhadran Baladandayuthapani - UT MD Anderson Cancer Center (United States)
Francesco Stingo - University of Florence (Italy) [presenting]
Abstract: Multidimensional data constituted by measurements along multiple axes have emerged across many scientific areas such as genomics and cancer surveillance. Traditional multivariate approaches are unsuitable for such highly structured data due to inefficiency, loss of power and lack of interpretability. We illustrate a novel class of multidimensional graphical models that includes both directed and undirected graphs as well as arbitrary combinations of these.
