Time-Varying DBN Inference with the ARTIVA (Auto Regressive TIme VArying) Model

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Description

This package generates Reversible Jump MCMC (RJ-MCMC) sampling for approximating the posterior distribution of a time varying regulatory network, under the Auto Regressive TIme VArying (ARTIVA) model (for a detailed description of the algorithm, see Lebre et al. BMC Systems Biology, 2010).

Starting from time-course gene expression measurements for a gene of interest (referred to as "target gene") and a set of genes (referred to as "parent genes") which may explain the expression of the target gene, the ARTIVA procedure identifies temporal segments for which a set of interactions occur between the "parent genes" and the "target gene". The time points that delimit the different temporal segments are referred to as changepoints (CP).

Details

Package: ARTIVA
Type: Package
Version: 1.2.3
Date: 2015-05-19
License: GPL (>=2)
LazyLoad: yes

Author(s)

S. Lebre and G. Lelandais.

Maintainer: S. Lebre <sophie.lebre@icube.unistra.fr>.

References

Statistical inference of the time-varying structure of gene-regulation networks S. Lebre, J. Becq, F. Devaux, M. P. H. Stumpf, G. Lelandais, BMC Systems Biology, 2010, 4:130.