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).


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install.packages("ARTIVA")

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