Docker container for Iso2Flux
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Version: 0.2

Short Description

Open source software for steady state 13C flux analysis


Iso2Flux is a Python-based flux analysis software that allows to perform 13C Metabolic Flux Analysis on a sub-network of a large scale model. Iso2flux uses constraint-based modelling to compute steady state fluxes across a large metabolic network and uses such flxues to predict 13C distribution across a subser of the newtork. Then, given a set of 13C data Iso2flux can iteratively find the steady state flux distributions that are most consistent with such fluxes.

Key features

  • Constraint-Based Modelling
  • 13C Metabolic Flux Analysis


  • Post-processing
  • Statistical Analysis
  • Workflows


  • Isotopic Labelling Analysis / 13C

Instrument Data Types

  • MS


Tool Authors

  • Carles Foguet (University of Barcelona)
  • Pedro de Atauri (University of Barcelona)
  • Vitaly Selinvanov (University of Barcelona)
  • Marta Cascante (Univesity of Barcelona)

Container Contributors


Git Repository

Usage Instructions

Iso2flux takes the following inputs: experimental_data_file= Name of the processed Metabolights file containing isotopologues distribution. tracing_model= Name of the file(s) describing the label propagation model. Should either be a xlsx file with 2 tabs (one for defining metabolites where label can be simulated and one describing reactions that can propagate label) or 2 CSV files containing the same information (the two files names should be in a string separated by a coma) sbml_model= Name of the SBML file describing the constraint based model that will be used time= Incubation time that will be evaluated factor= Experimental factor or condition that will be evaluated parameters= Name of the CSV file defining additional parameters for Iso2flux (Optional) constraints= Name of the file containing additional constraints for the constraint model (Optional) quick_analysis Disables the confidence interval analysis (Optional) Iso2Flux generates the follwing outputs: unconstrained_fluxes.csv:Flux variability analysis before tracer data is integrated best_label.csv:The simulated label distribution that is most consistent with experimental measurements best_fluxes.csv:The flux distribution that is most consistent with experimental measurments confidence.csv:The lower and upper limits of the confidence intervals


  • Carles Foguet, Pedro de Atauri, Vitaly A. Selivanov, Marta Cascante. Iso2Flux: A new software for 13C fluxomics developed in the framework of PhenoMeNal