ARTIVA (1.2.3)

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

http://cran.r-project.org/web/packages/ARTIVA

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).

Maintainer: Sophie Lebre
Author(s): S. Lebre and G. Lelandais.

License: GPL (>= 2)

Uses: gplots, igraph, MASS

Released over 4 years ago.


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