dummy variables in simbiology
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micronaut
am 4 Sep. 2016
Kommentiert: Arthur Goldsipe
am 8 Sep. 2016
Hi,
I have a model in simbiology where I am using a dummy parameter to control the concentration of an inhibitor in a reaction (michaelis-menten inhibitor function).
Basically, I have a rate rule controlling the concentration of the inhibitor species that sets it to 0 at a certain time, and this instantaneous change to 0 is controlled by the dummy parameter "event" (time>=24 & event == 1) which enables me to run my model according to 2 sets of experimental configurations; with and without the event.
I want to fit this model against experimental data in which 1 of the columns in my data set contains a 0 or 1 depending on whether the event was performed.
Is it possible to fit the model parameters using the "fit data" task, setting it up such that the dummy "event" parameter I have placed in the model is set using the value 0 or 1 in the column in the data set? (i.e IF data = 1, event = 1).
I use IF statements with dummy parameter values as switches quite a lot to control parameter and variable values when modelling with Matlab itself, is there a recommended way of doing this in simbiology so they can be coupled with values in specific data set columns for fitting?
Thanks for any help.
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Arthur Goldsipe
am 6 Sep. 2016
Hi,
Currently (as of R2016a), the data in a fit task can only affect a model via dosing. So I think you could do what you want if you change your dummy parameter to a dummy species and configure the fit task to use the 0/1 data column as dosing for this species.
-Arthur
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Arthur Goldsipe
am 8 Sep. 2016
I don't fully understand this question: "If I map washout to another species could they mapped together with inhibitor and washout?" Can you explain in a little more detail or provide an example. What is "they" in the sentence?
Regarding mapping the value of a parameter to a value in the data: Today, this is not possible in SimBiology. As I mentioned, you can only map the data to dosing information that is applied to the model.
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