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Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/17430
Título

DOTcvpSB, a software toolbox for dynamic optimization in systems biology

AutorHirmajer, Tomáš; Balsa-Canto, Eva ; Banga, Julio R.
Palabras claveDOTcvpSB
MIDO
MATLAB
SBML
Fecha de publicación29-jun-2009
EditorBioMed Central
CitaciónBMC Bioinformatics 10:199 (2009)
Resumen[Background] Mathematical optimization aims to make a system or design as effective or functional as possible, computing the quality of the different alternatives using a mathematical model. Most models in systems biology have a dynamic nature, usually described by sets of differential equations. Dynamic optimization addresses this class of systems, seeking the computation of the optimal time-varying conditions (control variables) to minimize or maximize a certain performance index. Dynamic optimization can solve many important problems in systems biology, including optimal control for obtaining a desired biological performance, the analysis of network designs and computer aided design of biological units.
[Results] Here, we present a software toolbox, DOTcvpSB, which uses a rich ensemble of state-of-the-art numerical methods for solving continuous and mixed-integer dynamic optimization (MIDO) problems. The toolbox has been written in MATLAB and provides an easy and user friendly environment, including a graphical user interface, while ensuring a good numerical performance. Problems are easily stated thanks to the compact input definition. The toolbox also offers the possibility of importing SBML models, thus enabling it as a powerful optimization companion to modelling packages in systems biology. It serves as a means of handling generic black-box models as well.
[Conclusion] Here we illustrate the capabilities and performance of DOTcvpSB by solving several challenging optimization problems related with bioreactor optimization, optimal drug infusion to a patient and the minimization of intracellular oscillations. The results illustrate how the suite of solvers available allows the efficient solution of a wide class of dynamic optimization problems, including challenging multimodal ones. The toolbox is freely available for academic use.
Descripción14 pages, 8 figures, 2 tables.
Versión del editorhttp://dx.doi.org/10.1186/1471-2105-10-199
URIhttp://hdl.handle.net/10261/17430
DOI10.1186/1471-2105-10-199
ISSN1471-2105
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