CRAN

ARTIVA 1.2.2

Infer a time-varying DBN network from time series data.

Released Sep 9, 2013 by S. Lebre and G. Lelandais.

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Dependencies

gplots 2.11.3 MASS 7.3-29 igraph 0.6.5-2

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).

Source

R

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