This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL).
|Author||M. Morris, T. Cokelaer|
|Date of publication||None|
|Maintainer||T. Cokelaer <firstname.lastname@example.org>|
CNORfuzzy-package: R version of CNOFuzzy, a Constrained Fuzzy Logic Network...
CNORwrapFuzzy: CNORfuzzy analysis wrapper
compileMultiRes: Compiles results from multiple runs and produces graph for...
computeScoreFuzzy: Compute Score of a model compared to the data for a given...
defaultParametersFuzzy: Create a list of default parameters
gaDiscreteT1: Genetic algorithm used to optimise a cFL model
getRefinedModel: Refinement of Parameters of cFL model
interpretDiscreteGA: Interpreter of output of discrete genetic algorithm
plotMeanFuzzyFit: Simulates models returned from multiple cFL runs and plots...
prep4simFuzzy: Prepare a model for simulation
reduceFuzzy: Remove unnecessary interactions from cFL model
simFuzzyT1: Simulation of a cFL model
writeFuzzyNetwork: Despict the network results of training a cFL model to data...