exhaustive: Exhaustive search over the optimisation of a PKN model on...

In saezlab/CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

Exhaustive search over the optimisation of a PKN model on MIDAS data.

Description

This function performs an exhaustive search of the parameter space tring all the solutions. It is used internally by the genetic algorithm when a small model has to be optimised and the number of solutions to try is smaller than the number of iterations that the Genetic Algorithm will perform.

Usage

exhaustive(CNOlist, model, shuffle=FALSE, Nmax=NULL, verbose=TRUE, sizeFac =
0.0001, NAFac = 1, relTol=0.1, timeIndex=2)

Arguments

CNOlist	a CNOlist on which the score is based (based on valueSignals[[2]], i.e. data at time 1)
model	a model structure, as created by readSIF, normally pre-processed but that is not a requirement of this function
shuffle	The list of bitstrings is set up arbitrarely. You may want to shuffle it.
Nmax	The total number of computation will be 2 to the power N, where N is the size of the model (ReacID field). The total number of computation can be large. You may want to set a maximumn number of computation using Nmax.
sizeFac	the scaling factor for the size term in the objective function, default to 0.0001
NAFac	the scaling factor for the NA term in the objective function, default to 1
relTol	the relative tolerance for the best bitstring reported by the genetic algorithm, i.e., how different from the best solution, default set to 0.1 Not yet implemented.
verbose	logical (default to TRUE) do you want the statistics of each generation to be printed on the screen?
timeIndex	the index of the time point to optimize. Must be greater or equal to 2 (1 corresponds to time=0). Must be less than the number of time points. Default is 2.

Value

This function returns a list with elements:

bString	the best bitstring
bScore	the best score
all_scores	all scores that have been computed
results	a matrix with columns "Generation","Best_score","Best_bitString","Stall_Generation","Avg_Score_Gen","Best_score_Gen","Best_bit_Gen","Iter_time"
stringsTol	the bitstrings whose scores are within the tolerance
stringsTolScores	the scores of the above-mentioned strings

Note that the field results, is not yet populated but maybe in the future.

Author(s)

T. Cokelaer

See Also

gaBinaryT1

Examples

data(CNOlistToy,package="CellNOptR")
data(ToyModel,package="CellNOptR")

#pre-process model

model = preprocessing(CNOlistToy, ToyModel)

#optimise

results <-exhaustive(
	CNOlist=CNOlistToy,
	model=model,
    shuffle=TRUE,
    Nmax=1000,
	verbose=FALSE)

saezlab/CellNOptR documentation built on April 16, 2024, 5:21 a.m.