Package: qpgraph
Title: Reverse engineering of molecular regulatory networks with
        qp-graphs
Version: 1.8.2
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: methods
Imports: methods, annotate, Matrix, graph, Biobase, 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: 2011-10-06 19:16:39 UTC; biocbuild
Built: R 2.13.2; i386-pc-mingw32; 2011-10-07 01:22:50 UTC; windows
Archs: i386, x64
