generate.data.maillard {CausalKinetiX}R Documentation

Maillard reaction

Description

Generate sample data from the Maillard reaction as specified by Bio52 in the BioModel data base.

Usage

generate.data.maillard(target, env = rep(1, 10), L = 15,
  par.noise = list(noise.sd = 0.01, only.target.noise = FALSE, relativ =
  FALSE), intervention = "initial_blockreactions",
  ode.solver = "lsoda", seed = NA, silent = FALSE)

Arguments

target

specifies which species is used as a target, needs to be an integer between 1 and 11.

env

integer vector of length n encoding to which experiment each repetition belongs.

L

number of time points for evaluation.

par.noise

list of parameters that specify the added noise. noise.sd specifies the standard deviation of noise, only.target.noise specifies whether to only add noise to target and relative specifies if the size of the noise should be relative to size of variable (if TRUE standard deviation is given by par.noise$noise.sd*(x(t)-x(t-1))).

intervention

string specifying type of intervention. Currently three type of interventions are implemented "initial" (only intervene on intial values), "blockreactions" (intervene by blocking random reactions) or "intial_blockreactions" (intervene on both initial values and blockreactions").

ode.solver

specifies which ODE solver to use when solving ODE. Should be one of the methods from the deSolve package ("lsoda", "lsode", "lsodes", "lsodar", "vode", "daspk", "euler", "rk4", "ode23", "ode45", "radau", "bdf", "bdf_d", "adams", "impAdams", "impAdams_d", "iteration").

seed

random seed. Does not work if a "Detected blow-up" warning shows up.

silent

set to TRUE if no status output should be produced.

Details

For further details see the references.

Value

list consisting of the following elements

simulated.data

D-matrix of noisy data.

time

vector containing time points

env

vector specifying the experimental environment.

simulated.model

object returned by ODE solver.

true.model

vector specifying the target equation model.

target

target variable.

Author(s)

Niklas Pfister, Stefan Bauer and Jonas Peters

References

Pfister, N., S. Bauer, J. Peters (2018). Identifying Causal Structure in Large-Scale Kinetic Systems ArXiv e-prints (arXiv:1810.11776).

Brands C. and van Boekel M. (2002). Kinetic modeling of reactions in heated monosaccharide-casein systems. Journal of agricultural and food chemistry, 50(23):6725–6739.

See Also

The functions generate.data.hidden and generate.data.targetmodel allow to simulate ODE data from two additional models.

Examples


simulation.obj <- generate.data.maillard(target=1,
                                         env=rep(1:5, 3),
                                         L=15)

D <- simulation.obj$simulated.data
fulldata <- simulation.obj$simulated.model
time <- simulation.obj$time
plot(fulldata[[1]][,1], fulldata[[1]][,2], type= "l", lty=2,
     xlab="time", ylab="concentration")
points(time, D[1,1:length(time)], col="red", pch=19)
legend("topright", c("true trajectory", "observations"),
       col=c("black", "red"), lty=c(2, NA), pch=c(NA, 19))

[Package CausalKinetiX version 0.2.1 Index]