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Flux balance analysis and its applications

The availability of annotated genome sequences has enabled the reconstruction of genome-scale metabolic networks for an increasing number of microorganisms. A popular and efficient method to study the characteristics and capabilities of such large-scale biochemical networks is flux balance analysis (FBA). In this tutorial we introduce the mathematical backgrounds of FBA and related methods, and present some of its recent biological applications ranging from biotechnology to evolutionary biology.

Proposed content

• Genome-scale metabolic reconstructions and their computational analyses.

• The constrained based approach to simulate large-scale models. Mathematical modelling and constrained optimisation. The basic idea of FBA.

• Using FBA to calculate growth properties and the effect of gene deletions in microbes. Experimental validation of computational predictions.

• Examples on the application of FBA in biotechnology.

• Application of FBA to understand genome evolution.

• Mathematics behind FBA: Linear Programming (LP) and Mixed Integer Linear Programming (MILP) formulations.

• LP solvers: the Simplex Method.

• MILP solvers.

• FBA as an LP problem.

• Mathematical examples.

Author information

Correspondence to Balazs Papp.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Keywords

  • Metabolic Network
  • Gene Deletion
  • Linear Programming Problem
  • Biological Application
  • Medical Topic