Package: ddepn
Type: Package
Title: Dynamic Deterministic Effects Propagation Networks: Infer
        signalling networks for timecourse RPPA data.
Version: 2.2
Date: 2011-06-27
Author: Christian Bender
Maintainer: Christian Bender <christian.bender@tron-mainz.de>
Depends: R (>= 2.14), lattice, coda, igraph, graph
Suggests: parallel, Rgraphviz, BoolNet
Imports: genefilter, gam, gplots
Description: DDEPN (Dynamic Deterministic Effects Propagation Networks): Infer signalling networks for timecourse data. Given a matrix of high-throughput genomic or proteomic timecourse data, generated after external perturbation of the biological system, DDEPN models the time-dependent propagation of active and passive states depending on a network structure. Optimal network structures given the experimental data are reconstructed. Two network inference algorithms can be used: inhibMCMC, a Markov Chain Monte Carlo sampling approach and GA, a Genetic Algorithm network optimisation. Inclusion of prior biological knowledge can be done using different network prior models.
License: GPL (>= 2)
LazyLoad: TRUE
Repository: CRAN
Repository/R-Forge/Project: ddepn
Repository/R-Forge/Revision: 85
Repository/R-Forge/DateTimeStamp: 2013-08-12 21:48:26
Date/Publication: 2013-08-13 08:41:00
Packaged: 2013-08-12 22:20:30 UTC; rforge
NeedsCompilation: yes
