BoolNet (version 1.44)

simplifyNetwork: Simplify the functions of a synchronous, asynchronous, or probabilistic Boolean network

Description

Eliminates irrelevant variables from the inputs of the gene transition functions. This can be useful if the network was generated randomly via generateRandomNKNetwork or if it was perturbed via perturbNetwork.

Usage

simplifyNetwork(network, readableFunctions = FALSE)

Arguments

network

A network structure of class BooleanNetwork or ProbabilisticBooleanNetwork. These networks can be read from files by loadNetwork, generated by latex{ }

readableFunctions

If this is true, readable DNF representations of the truth tables of the functions are generated. These DNF are displayed when the network is printed. The DNF representations are not minimized and can thus be very long. If set to FALSE, the truth table re

Value

• The simplified network of class BooleanNetwork or ProbabilisticBooleanNetwork. These classes are described in more detail in loadNetwork.

Details

The function checks whether the output of a gene transition function is independent from the states of any of the input variables. If this is the case, these input variables are dropped, and the transition function is shortened accordingly.

In non-probabilistic Boolean networks (class BooleanNetwork), constant genes are automatically fixed (e.g. knocked-out or over-expressed). This means that they are always set to the constant value, and states with the complementary value are not considered in transition tables etc. If you would like to change this behaviour, use fixGenes to reset the fixing.

See Also

loadNetwork,generateRandomNKNetwork, perturbNetwork, reconstructNetwork, fixGenes

Examples

library(BoolNet)

# load example data
data(cellcycle)

# perturb the network
perturbedNet <- perturbNetwork(cellcycle, perturb="functions", method="shuffle")
print(perturbedNet$interactions)

# simplify the network
perturbedNet <- simplifyNetwork(perturbedNet)
print(perturbedNet$interactions)