CLL                     Expression data from healthy and malignant
                        (chronic lymphocytic leukemia, CLL) human
                        B-lymphocytes after B-cell receptor stimulation
                        (GSE 39411 dataset)
CascadeFinit            Create initial F matrices for cascade networks
                        inference.
CascadeFshape           Create F matrices shaped for cascade networks
                        inference.
IndicFinit              Create initial F matrices using specific
                        intergroup actions for network inference.
IndicFshape             Create F matrices using specific intergroup
                        actions for network inference.
M                       Simulated microarray.
Net                     Simulated network for examples.
Net_inf_PL              Reverse-engineered network of the M and Net
                        simulated data.
Patterns-package        The Patterns Package
Selection               Selection of genes.
analyze_network         Analysing the network
as.micro_array          Coerce a matrix into a micro_array object.
clustExploration        A function to explore a dataset and cluster its
                        rows.
clustInference          A function to explore a dataset and cluster its
                        rows.
compare-methods         Some basic criteria of comparison between
                        actual and inferred network.
cutoff                  Choose the best cutoff
dim                     Dimension of the data
evolution               See the evolution of the network with change of
                        cutoff
geneNeighborhood        Find the neighborhood of a set of nodes.
genePeakSelection       Methods for selecting genes
gene_expr_simulation    Simulates microarray data based on a given
                        network.
inference               Reverse-engineer the network
infos                   Details on some probesets of the
                        affy_hg_u133_plus_2 platform.
methods                 Overview of a micro_array object
micro_array-class       Class '"micro_array"'
micropredict-class      Class '"micropred"'
network                 A example of an inferred network (4 groups
                        case).
network-class           Class '"network"'
network2gp              A example of an inferred cascade network (2
                        groups case).
networkCascade          A example of an inferred cascade network (4
                        groups case).
network_random          Generates a network.
plot-methods            Plot
plotF                   Plot functions for the F matrices.
position                Retrieve network position for consistent
                        plotting.
position-methods        Returns the position of edges in the network
predict                 Methods for Function 'predict'
print-methods           ~~ Methods for Function 'print' ~~
probeMerge              Function to merge probesets
replaceBand             Replace matrix values by band.
replaceDown             Replace matrix values triangular lower part and
                        by band for the upper part.
replaceUp               Replace matrix values triangular upper part and
                        by band for the lower part.
summary-methods         ~~ Methods for Function 'summary' ~~
unionMicro-methods      Makes the union between two micro_array
                        objects.
unsupervised_clustering
                        Cluster a micro_array object: performs the
                        clustering.
unsupervised_clustering_auto_m_c
                        Cluster a micro_array object: determine optimal
                        fuzzification parameter and number of clusters.
