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 trade-off between inluding and removing reactions based on their given weights. If desired, accumulation of certain metabolites can be allowed or even forced.


tissueModel = INIT(model, weights, tol, runtime, logfile)


  • 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 1e-8)
  • 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)


  • tissueModel – extracted model

Agren et al. (2012). Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT. PLoS Comput. Biol. 8, e1002518.