DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis

Background Dynamic Flux Balance Analysis (DFBA) is a dynamic simulation framework for biochemical processes. DFBA can be performed using different approaches such as static optimization (SOA), dynamic optimization (DOA), and direct approaches (DA). Few existing simulators address the theoretical and...

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Vydáno v:BMC bioinformatics Ročník 15; číslo 1; s. 409
Hlavní autoři: Gomez, Jose A, Höffner, Kai, Barton, Paul I
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 18.12.2014
BioMed Central Ltd
Témata:
Algorithms
Bacteria - growth & development
Bacteria - metabolism
Bioinformatics
Biomedical and Life Sciences
Bioreactors
Biotechnology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer Simulation
Differential equations
Dynamic tests
Dynamical systems
Dynamics
Exchange
Fluxes
Life Sciences
Mathematical optimization
Matlab
Metabolic Networks and Pathways
Microarrays
Models, Theoretical
Networks analysis
Optimization
Simulators
Software
Systems Biology - methods
Lexicographic optimization
Linear programming
Dynamic flux balance analysis
Nonsmooth dynamic systems
ISSN:1471-2105, 1471-2105
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Shrnutí:Background Dynamic Flux Balance Analysis (DFBA) is a dynamic simulation framework for biochemical processes. DFBA can be performed using different approaches such as static optimization (SOA), dynamic optimization (DOA), and direct approaches (DA). Few existing simulators address the theoretical and practical challenges of nonunique exchange fluxes or infeasible linear programs (LPs). Both are common sources of failure and inefficiencies for these simulators. Results DFBAlab, a MATLAB-based simulator that uses the LP feasibility problem to obtain an extended system and lexicographic optimization to yield unique exchange fluxes, is presented. DFBAlab is able to simulate complex dynamic cultures with multiple species rapidly and reliably, including differential-algebraic equation (DAE) systems. In addition, DFBAlab’s running time scales linearly with the number of species models. Three examples are presented where the performance of COBRA, DyMMM and DFBAlab are compared. Conclusions Lexicographic optimization is used to determine unique exchange fluxes which are necessary for a well-defined dynamic system. DFBAlab does not fail during numerical integration due to infeasible LPs. The extended system obtained through the LP feasibility problem in DFBAlab provides a penalty function that can be used in optimization algorithms.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-014-0409-8