Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.4.1
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: 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: 2010-05-04 21:51:52 UTC; biocbuild
Built: R 2.11.0; x86_64-pc-mingw32; 2010-05-05 02:32:13 UTC; windows
