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  • Title: Identifying differentially expressed subnetworks with MMG.
    Author: Noirel J, Sanguinetti G, Wright PC.
    Journal: Bioinformatics; 2008 Dec 01; 24(23):2792-3. PubMed ID: 18819939.
    Abstract:
    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 http://www.dcs.shef.ac.uk/~guido/; the new implementation is available from http://wrightlab.group.shef.ac.uk/people_noirel.htm, from CRAN, and has been submitted to BioConductor, http://www.bioconductor.org/.
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