Description Usage Arguments Value Examples

View source: R/BNP_BooleanToODE.R

The function translate the Boolean Network to a Determinist Continuous Network composed by two principal parts. The first one containes the translation from classic to fuzzy logic using one of two methods. The second one contains an ODE-based description of the rate of changes for each of the nodes. IMPORTANT: This function call the perl script "ConvertTocontinuos.pl".

1 2 | ```
booleanToODE(net, logic = "Zadeh", eq = "SQUAD", sep = ",",
mutants = c(), keep.input = FALSE)
``` |

`net` |
BoolNet network |

`logic` |
is a character string specificating either if Zadeh or Probabilistic logic is employed during the translation. Default: Zadeh. |

`eq` |
is a character string specificating either if the equation proposed by Sanchez-Corrales et al., 2010 or Villarreal et al., 2012 is employed by describe the rate of change for the nodes in the network. |

`sep` |
between targets and factors in file, default "," |

`mutants` |
list of genes to mutate, the derivate will be 0 |

`keep.input` |
if TRUE set the derivate of the inputs to 0 |

Returns a list with func (ode function), parameters and example state and time. The parameters are a vector where h=10, w=0.5 and decay rate = 1.

1 2 3 4 5 6 7 8 | ```
library(deSolve)
data(cellcycle)
net.ode <- booleanToODE(cellcycle)
ode(func = net.ode$func,
parms = net.ode$parameters,
y = net.ode$state,
times = seq(0, 5, 0.1))
``` |

mar-esther23/boolnet-perturb documentation built on Jan. 14, 2019, 7:49 p.m.

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