Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separ...
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...