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

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).


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.2.3 by S. Lebre, 4 years ago

Browse source code at https://github.com/cran/ARTIVA

Authors: S. Lebre and G. Lelandais.

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on MASS, igraph, gplots

See at CRAN