Infer a time-varying DBN network from time series data 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). Software Depends: MASS, igraph S. Lebre <sophie.lebre@lsiit-cnrs.unistra.fr> S. Lebre and G. Lelandais. GPL (>= 2) 2011-12-20 application/tgz http://CRAN.R-project.org/package=ARTIVA