Bioinformatics Advance Access published online on December 10, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn637
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SIMoNe: Statistical Inference for MOdular NEtworks
UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Évry, FRANCE
*To whom correspondence should be addressed. Dr. Julien Chiquet, E-mail: julien.chiquet{at}genopole.cnrs.fr
| Abstract |
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Summary: The R package SIMoNe enables inference of generegulatory networks based on partial correlation coefficients from microarray experiments. Modelling gene expression data with a Gaussian Graphical Model (hereafter GGM), the algorithm estimates nonzero 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/
Contact: julien.chiquet{at}genopole.cnrs.fr
Associate Editor: Prof. John Quackenbush
Received on October 23, 2008; revised on December 4, 2008; accepted on December 6, 2008