gaBinaryT2: Genetic algorithm for time point 2

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

Description

This is the genetic algorithm for time point 2, that should follow optimisation based on time point 1.

Deprecated in version 1.3.28. Use gaBinaryTN instead.

Usage

gaBinaryT2(CNOlist, model,  bStringT1, sizeFac = 1e-04, NAFac = 1,
popSize = 50, pMutation = 0.5, maxTime = 60, maxGens = 500,
stallGenMax = 100, selPress = 1.2, elitism = 5, relTol = 0.1, verbose=TRUE,
priorBitString=NULL )

Arguments

CNOlist	a CNOlist on which the score is based (based on valueSignals[[3]], i.e. data at t2)
model	a model structure, as created by readSIF, normally pre-processed but that is not a requirement of this function
bStringT1	the optimal bitstring from optimisation at time 1 (i.e. a vector of 0s and 1s)
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
popSize	the population size for the genetic algorithm, default set to 50
pMutation	the mutation probability for the genetic algorithm, default set to 0.5
maxTime	the maximum optimisation time in seconds, default set to 60
maxGens	the maximum number of generations in the genetic algorithm, default set to 500
stallGenMax	the maximum number of stall generations in the genetic algorithm, default to 100
selPress	the selective pressure in the genetic algorithm, default set to 1.2
elitism	the number of best individuals that are propagated to the next generation in the gen. al. default set to 5
relTol	the relative tolerance for the best bitstring reported by the genetic algorithm, i.e.how different from the best solution can solutions be to be reported as well, default set to 0.1
verbose	logical (default to TRUE) do you want the statistics of each generation to be printed on the screen
priorBitString	A bitString of same length at the initial bitstring made of 0, 1 or NA. By default, this bitstring is set to NULL (equivalent to setting all bits to NA). If provided, all bitstring in a population will be changed to be in agreement with the priorBitString list.

Details

This function takes in the same input as the T1 ga, but in addition it takes in the bitstring optimised for T1, and does not take an initial bitstring. Be aware that the bitString that this function returns is one that only includes the bits that it actually looks at, i.e. the bits that were 0 in the bStringT1

Value

This function returns a list with elements:

bString	the best bitstring
bScore	the best score
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-mentionned strings

Author(s)

C.Terfve, T. Cokelaer

See Also

getFit, prep4sim, indexFinder, simulatorT1, simulatorT2, gaBinaryT2

Examples

#load data

data(CNOlistToy2,package="CellNOptR")
data(ToyModel2,package="CellNOptR")

#pre-process model

checkSignals(CNOlistToy2,ToyModel2)
model = preprocessing(CNOlistToy2, ToyModel2)

#optimise t1
ToyT1<-gaBinaryT1(
	CNOlist=CNOlistToy2,
	model=model,
	maxGens=10,
	popSize = 10,
	verbose=FALSE)

#Optimise T2

ToyT2<-gaBinaryT2(
	CNOlist=CNOlistToy2,
	model=model,
	bStringT1=ToyT1$bString,
	maxGens=10,
	popSize = 10,
	verbose=FALSE)

CellNOptR documentation built on Nov. 8, 2020, 6:58 p.m.