SIMoNe: Statistical Inference for MOdular NEtworks

@article{Chiquet2009SIMoNeSI,
  title={SIMoNe: Statistical Inference for MOdular NEtworks},
  author={Julien Chiquet and Alexander Smith and Gilles Grasseau and Catherine Matias and Christophe Ambroise},
  journal={Bioinformatics},
  year={2009},
  volume={25 3},
  pages={
          417-8
        }
}
SUMMARY The R package SIMoNe (Statistical Inference for MOdular NEtworks) enables inference of gene-regulatory networks based on partial correlation coefficients from microarray experiments. Modelling gene expression data with a Gaussian graphical model (hereafter GGM), the algorithm estimates non-zero entries of the concentration matrix, in a sparse and possibly high-dimensional setting. Its originality lies in the fact that it searches for a latent modular structure to drive the inference… CONTINUE READING

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