| Literature DB >> 19073589 |
Julien Chiquet1, Alexander Smith, Gilles Grasseau, Catherine Matias, Christophe Ambroise.
Abstract
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 procedure through adaptive penalization of the concentration matrix. AVAILABILITY: Under the GNU General Public Licence at http://cran.r-project.org/web/packages/simone/Entities:
Mesh:
Year: 2008 PMID: 19073589 DOI: 10.1093/bioinformatics/btn637
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937