LeMoNe is a software package for Learning Module Networks from gene expression data. The algorithm has been described and validated in the following papers:

  1. * 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
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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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