writeObjectiveFunction: Writing the objective function for the ILP implementation of...

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

Description

This function takes as input the integer variables assigned to each of the elements in the network and data in a CNOlist object in order to produce the objective function needed to be optimized by the ILP solver.

Usage

writeObjectiveFunction <- function(model, 
                                   midasExperimentPart, 
                                   y_vector=y_vector,
                                   accountForModelSize = TRUE, 
                                   sizeFac = .000001, 
                                   meansOfMeasurements_at_t0, 
                                   method = "quadratic" )

Arguments

model	the model
midasExperimentPart	the experimental part of CNOlist where data is stored
y_vector	the variables for each interaction in the PKN
accountForModelSize	the verbose variable if we wish to apply the size penalty
sizeFac	the size penalty factor
meansOfMeasurements_at_t0	the means of measurements at time-point 0
method	the method of defining the objective function ("quadratic/linear")

Author(s)

E Gjerga, H Koch

References

Alexander Mitsos, Ioannis N. Melas, Paraskeuas Siminelakis, Aikaterini D. Chairakaki, Julio Saez-Rodriguez, and Leonidas G. Alexopoulos. Identifying Drug Effects via Pathway Alterations using an Integer Linear Programming Optimization Formulation on Phosphoproteomic Data. PLoS Comput Biol. 2009 Dec; 5(12): e1000591.

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