INIT¶

INIT
(model, weights, tol, runtime, logfile, epsilon)[source]¶ Use the INIT algorithm (Agren et al., 2012) to extract a context specific model using data. INIT algorithm find the optimal tradeoff between inluding and removing reactions based on their given weights. If desired, accumulation of certain metabolites can be allowed or even forced.
Usage
tissueModel = INIT(model, weights, tol, runtime, logfile)Inputs
 model – input model (COBRA model structure)
 weights – column with positive and negative weights for each reaction positive weights are reactions with high expression, negative weigths for reaction with low expression (must be same length as model.rxns)
Optional inputs
 tol – minimum flux threshold for “expressed” reactions (default 1e8)
 logfile – name of the file to save the MILP log (string)
 runtime – maximum solve time for the MILP (default value  7200s)
 epsilon – value added/subtracted to upper/lower bounds (default 1)
Output
 tissueModel – extracted model
Agren et al. (2012). Reconstruction of genomescale active metabolic networks for 69 human cell types and 16 cancer types using INIT. PLoS Comput. Biol. 8, e1002518.