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DOTcvpSB, a software toolbox for dynamic optimization in systems biology

Tomáš Hirmajer12, Eva Balsa-Canto1 and Julio R Banga1*

Author Affiliations

1 Instituto de Investigaciones Marinas, IIM-CSIC, Spanish Council for Scientific Research, C/Eduardo Cabello 6, 36208 Vigo, Spain

2 Institute of Neuroimmunology, Slovak Academy of Sciences, Dúbravská 9, 845 10 Bratislava, Slovak Republic

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BMC Bioinformatics 2009, 10:199  doi:10.1186/1471-2105-10-199

Published: 29 June 2009



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.


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.


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.