Title: Infer a time-varying DBN network from time series data.
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).

Title: What the package does (short line)
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

Title: Time-Varying DBN Inference with the ARTIVA (Auto Regressive TIme
Description: 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