parameter estimation in a model when we have some time courses

HI there,

Q1: i'm wondering if there are two distinct ODE models and each representing a biological system that may have some relationship together (for example cell cycle pathway and apoptosis pathway), is it possible to mix them in one model using the parameters and initial values same as the original model (without changing the parameters)? Because there are some mutual elements in these models, the modelers made some assumption to get a correct dynamics. So, when you combine the two model, the dynamic of a particular element (X) will be different (incorrect).

Q2: My question is that since the dynamics of element X in each of these single models is correct, is it possible to give the correct time course (dynamic) of X to SIMBIOLOGY in order to have the correct dynamic at last(and Simbiology probably fine-tunes some other parameters)?

Q3: Is it possible that this process makes the dynamics of other species in the model incorrect?

Q4: And another question is that if it is possible to fix some parameters (known parameters) and want Simbiology to just estimate the unknown parameters (and we may have the dynamics of some of the species but not all)? Q5: I remember that I tried to give one time course (of one specie) to simbilogy but the answer was quite wrong! DO you know why it may happens?

Answer 1

[Arthur Goldsipe]

Hi Ali,

The short answers to your questions are: Yes, Yes, Yes, Yes, and Yes.

The long answer is that these are extremely complicated questions that can't easily be answered here. In fact, one of my colleagues basically did his PhD work on such questions. The general answer to your general question is that almost anything is possible.

That said, let me see if I can tell you how MATLAB and SimBiology can help you with these sorts of problems:

The SimBiology Desktop will let you merge two models by copying the relevant model elements in the diagram and pasting them in a new model. However, you will then have to manually reconfigure the merged model to ensure that the common elements are connected correctly.

SimBiology will also let you estimate parameter values if your model by trying to fit the model to experimental data. Because this is such a challenging task, SimBiology provides multiple approaches and optimization algorithms to do this. From the command line, you can use functions like sbiofit and sbiofitmixed. From the SimBiology Desktop, you can create a Fit Task.

Even after fitting, there are lots of reasons your model might not give good results: The model could be missing some important biology. You might not have enough experimental data to constrain the model during fitting. It might be very difficult to find appropriate parameter values.