ARTIVA: 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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AuthorS. Lebre and G. Lelandais.
Date of publication2015-05-20 01:09:27
MaintainerS. Lebre <>
LicenseGPL (>= 2)

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ARTIVA Man page
ARTIVAnet Man page
ARTIVA-package Man page
ARTIVAsubnet Man page
ARTIVAsubnetAnalysis Man page
bdu Man page
buildXY Man page
choosePriors Man page
computePx Man page
computeRho3 Man page
computeRho4 Man page
cp.birth Man page
cp.computeAlpha Man page
cp.death Man page
CPposition Man page
CP.postDist Man page
cp.shift Man page
dinvgamma Man page
drosophila Man page
fast.svd Man page
geneNetworkSummary Man page
hasSeg Man page
init Man page
main Man page
nsmall.svd Man page
plotCP.postDist Man page
PlotFunction Man page
plotSegmentModel.postDist Man page
positive.svd Man page
priors Man page
pseudoinverse Man page
psmall.svd Man page
PSRF Man page
readDataTS Man page
readInput Man page
rinvgamma Man page
sampleBinit Man page
sampleBxy Man page
sampleDelta2 Man page
sampleK Man page
sampleParms Man page
sampleSig2 Man page
segmentModel.postDist Man page
segment.update Man page
segPos Man page
simulatedProfiles Man page
traceGeneProfiles Man page
traceNetworks Man page
updateSigMulti Man page
yeast Man page

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