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» Inferring Genetic Networks from Microarray Data
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BIOCOMP
2006
15 years 2 months ago
Theoretical Bounds for the Number of Inferable Edges in Sparse Random Networks
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...
Frank Emmert-Streib, Matthias Dehmer
BMEI
2008
IEEE
15 years 8 months ago
Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks
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...
Xiuwei Zhang, Maryam Zaheri, Bernard M. E. Moret
BMCBI
2007
130views more  BMCBI 2007»
15 years 1 months ago
A robust measure of correlation between two genes on a microarray
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...
AAAI
2011
14 years 1 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
AI
2007
Springer
15 years 7 months ago
Learning Network Topology from Simple Sensor Data
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...
Dimitri Marinakis, Philippe Giguère, Gregor...