Flux variability analysis

General concept

For a given level of the cellular objective (e.g., biomass yield). Upper and lower bounds of all steady state reaction fluxes can be determined. After setting the lower bound to a desired lower bound, each reaction flux is minimized and maximized to find its steady state bounds.

Items to consider when implementing

Software packages with this method

Applications of interest

Mahadevan and Schilling (2003) assessed alternate optimal solutions using the min-max optimization and coined the term "flux variability analysis".

Gudmundsson and Thiele (2010) proposed an algorithmic enhancement of FVA, called FastFVA, which significantly sped up implementation compared to previous FVA implementations.

Chen, et al. (2009) investigated the idea of analyzing flux variability at states below the optimal growth rate, and called this "Expanded flux variability analysis".

Relevant references

Burgard AP, Vaidyaraman S, Maranas CD. Minimal reaction sets for Escherichia coli metabolism under different growth requirements and uptake environments. Biotechnol Prog. 2001 Sep-Oct;17(5):791-7.

Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003 Oct;5(4):264-76.

Gudmundsson S, Thiele I. Computationally efficient flux variability analysis. BMC Bioinformatics. 2010 Sep 29;11:489.

Chen T, Xie ZW, Ouyang Q. Expanded flux variability analysis on metabolic network of Escherichia coli. Chinese Science Bulletin 2009 Vol. 54 (15): 2610-2619.

Related methods


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