Systems biology SIMoNe : Statistical Inference for MOdular NEtworks

  title={Systems biology SIMoNe : Statistical Inference for MOdular NEtworks},
  author={Julien Chiquet and Alexander Smith and Gilles Grasseau and Catherine Matias and Christophe Ambroise},
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