Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.12.2
Author: R. Castelo and A. Roverato
Description: q-order partial correlation graphs, or qp-graphs for short, are
             undirected Gaussian graphical Markov models built from q-order
             partial correlations. They are useful for learning undirected
             graphical Gaussian Markov models from data sets where the number of
             random variables p exceeds the available sample size n as, for
             instance, in the case of microarray data where they can be employed
             to reverse engineer a molecular regulatory network.
Depends: R (>= 2.10), methods
Imports: methods, annotate, Matrix, graph, Biobase, GGBase,
        AnnotationDbi
Enhances: rlecuyer, snow, Rgraphviz
Suggests: Matrix, mvtnorm, graph, genefilter, Category,
        org.EcK12.eg.db, GOstats
Maintainer: Robert Castelo <robert.castelo@upf.edu>
License: GPL (>= 2)
biocViews: Microarray, GeneExpression, Transcription, Pathways,
        Bioinformatics, GraphsAndNetworks
LazyLoad: yes
URL: http://functionalgenomics.upf.edu/qpgraph
Packaged: 2012-05-30 05:34:19 UTC; biocbuild
Built: R 2.15.0; i386-pc-mingw32; 2012-05-30 10:33:00 UTC; windows
Archs: i386, x64
