NOTE! The ICMg package is now included in the NetResponse R/BioC package. It is highly recommended to use the Netresponse package instead!
ICMg can be used to infer functional gene modules from combinations of protein-protein interaction (PPI) and gene expression data. Based on a probabilistic graphical model the method produces a component membership distribution for all genes. This can be interpreted as a clustering for the genes into modules. The method has been described in published in Searching for functional gene modules with interaction component models. The method has been developed by the Statistical Machine Learning and Bioinformatics group at the Department of Information and Computer Science, Aalto University. When you use this method, please cite the following paper:
Juuso Parkkinen and Samuel Kaski. Searching for functional gene modules with interaction component models. BMC Systems Biology 2010, 4:4. |
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