Identifying differentially expressed subnetworks with MMG

Josselin Noirel, Guido Sanguinetti, Phillip C. Wright

Research output: Contribution to journalArticlepeer-review


Background: 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.Availability: The original implementation (Matlab) is still available from; the new implementation is available from, from CRAN, and has been submitted to BioConductor,
Original languageEnglish
Pages (from-to)2792-2793
Number of pages2
Issue number23
Publication statusPublished - Dec 2008


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