This page provides references and software for the clustering method based on  Gaussian Infinite mixture models. The software consists of the R package gimmR and the self-standing software WinGimm. Linus and Windows versions of both gimmR and WinGimm are available as well as some basic documentations. You are free to use the code and software in any way you would like. However, if you do use and/or improve the code of the program, you have to make your code publicly available as specified in GNU General Public License. The model description of and performance comparisons can be found in following papers:

Liu X, Jessen W, Sivaganesan S, Aronow BJ, Medvedovic M: Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data. BMC Bioinformatics, 8(1):283. 2007.

Liu, X., Sivaganesan, S., Yeung, K.Y., Guo, J., Bumgarner, R.E., Medvedovic M. DNA Microarrays and Computational Analysis of DNA Microarray Data in Cancer Research. Bioinformatics 22:1737-44. 2006. (Support Page)(preprint)

Medvedovic M., Guo, J., Bayesian Model-Averaging in Unsupervised Learning From Microarray Data. BIOKDD 2004.

Medvedovic, M., Yeung, K.Y., Bumgarner, R.E. Bayesian Mixtures for Clustering Replicated Microarray Data. Bioinformatics. 20: 1222-1232, 2004.

Medvedovic M.,  Sivaganesan S.  Bayesian infinite mixture model based clustering of gene expression profiles.  Bioinformatics 18: 1194-1206, 2002.  

Yeung, K.Y., Medvedovic,M. Bumgarner, R.E. Clustering Gene Expression Data With Repeated Measurements. Genome Biology 4(5): R34. 2003.

If you have any troubles using the software, please contact me and I will be glad to assist you.