Experimental datasets, metabolic models and MATLAB scripts from the following manuscript:
R S Costa, S Nguyen, A Hartman, S Vinga "Exploring the cellular objective in flux balance constraint-based models", Lecture Notes in Computer Science: 8859, 211-224 (2014) | DOI:10.1007/978-3-319-12982-2_15
Matlab implementation for investigation the effect of cellular objective functions and constraints in flux balance constraint-based models. Implementation of all objective functions and constraints can be adapted to test different metabolic systems.
I. PREQUISITES
-MATLAB 2012b with Global Optimization Toolbox and Parallel Computing.
-Cobra toolbox 2.0.5 (GLPK+libSBML): http://opencobra.sourceforge.net/openCOBRA
II. CONTENT/INSTRUCTIONS
- Scripts:
-runall.m: control script to run all experiments in the paper.
-simulation.m: different FBA implementations go here.
-constraint_*.m: scripts to set up constraints for FBA.
-max/min*.m: objective functions.
-pareto*.m: pareto optimization with 2 or 3 objective functions. The algorithm being applied is epsilon-constraint [1]. Not used in the article.
- Data:
-./data/Expdata_ec_core_model.mat: experimental datasets containing mapped fluxes values from different data sources to the Core model.
-./dataExpdata_ec_schuetz_model.mat: experimental datasets containing mapped fluxes values from different data sources to the Schuetz model. Not used in the article.
-./dataExpdata_ec_iaf1260_model.mat: experimental datasets containing mapped fluxes values from different data sources to the iAF1260 genome-scale model.
- Models:
-./models/ec_core_model.mat: Matlab format for the Core model [2].
-./models/ec_schuetz_model.mat: Matlab format for the Schuetz model [3]. Not used in the article.
-./models/ec_iaf1260_model.mat: Matlab format for the Genome-scale model [4].
- Additional files
-./supp/matching.xlsx: Microsoft excel file containing the matching between experimental fluxes from different data sources to reactions in reconstruction models.
-./supp/plots.docx: Microsoft word file containing all figures generated.
III. REFERENCES
[1] Jahn, J.: Vector Optimization: Theory, Applications, and Extensions (Springer, Heidelberg, Germany, 2004).
[2] Orth, J.D, Fleming, R.M.T., Palsson, B.O.: Reconstruction and use of microbial metabolic networks: the core Escherichia coli metabolic model as an Educational Guide. In: Escherichia coli and Salmonella: Cellular and Modelcular Biology, ASM Press, edition 2010.
[3] Schuetz, R., Kuepfer, L., Sauer, U.: Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. Molecular Systems Biology 3, 119 (2007)
[4] Feist, A.M., Henry, C.S., Reed, J.L., Krunmenacker, M., Joyce, A.R., Karp, P.D. et al: A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Molecular Systems Biology, 3, 121(2007).