Abstract-- The inference of a network structure from experimental data providing dynamical information about the underlying system of investigation is an important and still outsta...
Inferring transcriptional regulatory networks from geneexpression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong networ...
Background: The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particula...
Johanna S. Hardin, Aya Mitani, Leanne Hicks, Brian...
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...