Lemone
 LeMoNe is a software package for Learning Module Networks from gene expression data. The algorithm has been described and validated in the following papers:
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* Michoel, T., * Maere, S., Bonnet, E., Joshi, A., Saeys, Y., Van den Bulcke, T., Van Leemput, K., van Remortel, P., Kuiper, M., Marchal, K., Van de Peer, Y. (2007)
Validating module networks learning algorithms using simulated data. BMC Bioinformatics 8 Suppl 2:S5. *contributed equally
- Joshi, A., Van de Peer, Y., Michoel, T. (2008)
Analysis of a Gibbs sampler method for model based clustering of gene expression data. Bioinformatics 24(2):176-83.
- Joshi, A., De Smet, R., Marchal, K., Van de Peer, Y., Michoel, T. (2009)
Module networks revisited: computational assessment and prioritization of model predictions. Bioinformatics 25(4):490-6.
- Michoel, T., De Smet, R., Joshi, A., Van de Peer, Y., Marchal, K. (2009)
Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks. BMC Syst. Biol. 3:49.
- Vermeirssen, V., Joshi, A., Michoel, T., Bonnet, E., Casneuf, T., Van de Peer, Y. (2009)
Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. Molecular BioSystems 5(12):1817-30.
- Bonnet, E., Tatari, M., Joshi, A., Michoel, T., Marchal, K., Berx, G., Van de Peer, Y. (2010)
Module network inference from a cancer gene expression data set identifies microRNA regulated modules. PLoS One 5(4):e10162.
- Bonnet, E., Michoel, T., Van de Peer, Y. (2010)
Prediction of a regulatory network linked to prostate cancer from gene expression, microRNA and clinical data. Bioinformatics 26(18):i638-44.
LeMoNe is freely available for academic use. We ask that you register here before downloading the software.
An extensive tutorial for LeMoNe can be downloaded here.
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