PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Identifying differentially expressed subnetworks with MMG
Josselin Noirel, Guido Sanguinetti and Phillip C. Wright
Bioinformatics Volume 24, Number 23, pp. 2792-2793, 2008.

Abstract

Mixture model on graphs (MMG) is a probabilistic model that integrates network topology with (gene, protein) expression data to predict the regulation state of genes and proteins. It is remarkably robust to missing data, a feature particularly important for its use in quantitative proteomics. A new implementation in C and interfaced with R makes MMG extremely fast and easy to use and to extend.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Theory & Algorithms
ID Code:4550
Deposited By:Guido Sanguinetti
Deposited On:13 March 2009

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