Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.2.0
Author: R. Castelo and A. Roverato
Description: q-order partial correlation graphs, or qp-graphs for
        short, are undirected Gaussian graphical Markov models that
        represent 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: methods, Biobase (>= 2.5.5), AnnotationDbi
Imports: methods, Biobase (>= 2.5.5), AnnotationDbi
Suggests: mvtnorm, graph, Rgraphviz, annotate, genefilter, Category (>=
        2.9.7), org.EcK12.eg.db (>= 2.2.6), GOstats
Maintainer: Robert Castelo <robert.castelo@upf.edu>
License: GPL (>= 2)
biocViews: Microarray, GeneExpression, Transcription, Pathways,
        Bioinformatics, GraphsAndNetworks
URL: http://functionalgenomics.upf.edu/qpgraph
Packaged: 2009-10-28 10:39:44 UTC; biocbuild
Built: R 2.10.0; i386-pc-mingw32; 2009-10-28 14:42:19 UTC; windows
