DOTcvpSB: a Matlab Toolbox for Dynamic Optimization in Systems Biology

Download DOTcvpSB toolbox for WINDOWS*
      DOTcvpSB_R2010_E4.zip gnumex and MinGW included [around 29 MB]      presentation      Documentation
DOTcvpSB_R2010_E4_small.zip without gnumex and MinGW [around 8 MB] Main modules description - check it out!
*The full functionality is guaranteed under the MATLAB version 7.0-7.7 [2008b]. The newest MATLAB versions do not support precompiled libraries for MITS, ACOmi, and MISQP.

Graphical user interface, step by step

The GUI for DOTcvp toolbox consists of several steps. The input screens for a Van der pol oscillator problem are shown here:
  1. Introduction screen, here the user can choose if he wants to create a new problem, or if he would like to continue editing the previously created problem.
    Introduction
  2. NLP Definition, here is set everything regarding the NLP settings, gradient method, cost function, and bounds on the control variables and on time-independent parameters, with a convenient approximation.
    NLP Definition
  3. Settings Related to the Initialization, NLP, and IVP, in this step it is needed to insert a problem name, select a compiler, and than the user can change the number of control, time-independent parameters, and state variables with initial and final time. If the free time problem is considered, there is a place to define the initial conditions for time variables.
    Initialization of the Optimization
  4. Problem Definition, there is a place for the definition of the model with the help of ordinary differential equations (ODEs), the initial conditions, and parameters for MATLAB or FORTRAN if they are used. The form how the ODEs have to be inserted is shown on the beginning of this screen.
    Problem Definition
  5. Equality and Inequality Constraints, place for the before mentioned constraints, if they are active, it is needed to set the switch on the value of 'on'. The violation of the constraints can be penalized directly with the help of the penalty coefficients. This option is obligatory for stochastic methods.
    In/Equality Constraints
  6. ODE and Sensitivities Initialization, this screen is used for the initialization (set the tolerance levels) of the integrated equations, both system and sensitivities.
    ODE and Sensitivities Initialization
  7. Output, the last screen. Here it is possible to set many settings for the output (figures and data). The most important option is to save the data into a .dotcvp file, which can be later used for the loading and editing of the problem. All presented problems in the report can be loaded and edited directly from the toolbox package as a .dotcvp file.
    Output
  8. MATLAB output: At the end of the optimization the graphic output can be obtained together with the numerical solution.
    MATLAB output