SIMoNe: Statistical Inference for MOdular NEtworks. - Archive ouverte HAL
Article Dans Une Revue Bioinformatics Année : 2009

SIMoNe: Statistical Inference for MOdular NEtworks.

Résumé

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/
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Dates et versions

hal-00592218 , version 1 (12-05-2023)

Identifiants

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Julien Chiquet, Alexander Smith, Gilles Grasseau, Catherine Matias, Christophe Ambroise. SIMoNe: Statistical Inference for MOdular NEtworks.. Bioinformatics, 2009, 25 (3), pp.417-418. ⟨10.1093/bioinformatics/btn637⟩. ⟨hal-00592218⟩
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