Reference

All functions
Cascade-package Cascade	The Cascade Package: Selection, Reverse-Engineering and Prediction in Cascade Networks
M	Simulated M data for examples.
Net	Simulated network data for examples.
Net_inf	Reverse-engineered network of the simulated data.
Selection	Selection of genes.
analyze_network(<network>)	Analysing the network
as.micro_array()	Coerce a matrix into a micro_array object.
compare(<network>,<network>,<numeric>)	Some basic criteria of comparison between actual and inferred network.
cutoff(<network>)	Choose the best cutoff
dim(<micro_array>)	Dimension of the data
evolution(<network>)	See the evolution of the network with change of cutoff
geneNeighborhood(<network>)	Find the neighborhood of a set of nodes.
geneSelection(<micro_array>,<micro_array>,<numeric>) geneSelection(<list>,<list>,<numeric>) genePeakSelection(<micro_array>,<numeric>)	Methods for selecting genes
gene_expr_simulation(<network>)	Simulates microarray data based on a given network.
head(<micro_array>)	Overview of a micro_array object
inference(<micro_array>)	Reverse-engineer the network
micro_array-class	Class "micro_array"
micropredict-class	Class "micropredict"
network-class	Class "network"
network	A network object data.
network_random()	Generates a network.
plot(<micro_array>,<ANY>) plot(<network>,<ANY>) plot(<micropredict>,<ANY>)	Plot
position(<network>)	Returns the position of edges in the network
predict(<micro_array>)	Prediction of the gene expressions after a knock-out experience predict
print(<micro_array>) print(<network>)	Methods for Function print
summary(<micro_array>)	Methods for Function summary
unionMicro(<micro_array>,<micro_array>)	Makes the union between two micro_array objects.