I can give my answer to this here and maybe someone in Auckland can
forward it the Steve as I'm not sure he is on this list.
> Steven Niederer wrote:
>> Hi guys,
>>
>> Just checking if there was any work been done on the following:
>>
>> 1) creating maps of variable names to allow a user (me) to define a
>> variable that I want to change in a one file and have that mapped onto
>> the corresponding variable in a model. (I am batch processing analysis
>> of 20+ models at the moment)
>>
>> ie I wish to set value for intracellular calcium. I want to call the
>> variable Cai but in the models that I have it is called cai, Cai and
>> Ca_i etc. so I wish to create a wrapper for each model to map the
>> variables to a standard name.
>> Is there any work been done on things like this and if so is their a
>> recommended format for the mapping wrapper?
this can be easily accomplished using CellML 1.1. If you want to have
all the models run at once you can import all the 20+ models into one
model and connect the various calcium variables to a single variable in
the mega model. Otherwise, if you want to keep the models independent
you create a wrapper for each model which imports the model and a common
calcium model which defines the common calcium value. This variable can
then be connected to each model in the wrapper model allowing you to
change it in just one place for all models.
This would, of course, work for any variable(s) in the models. An
applied electrical or mechanical stimulus would be another good example
of this.
>> 2) Defining virtual experiment protocols.
>>
>> After defining the model variables that I wish to set as model outputs
>> or inputs I would like to define how the input variables are set and
>> if I want any post processing to be done on my output signals.
>> Again I wondered if there was a proposed format for these types of
>> descriptions.
again - CellML 1.1 is perfect for this. You define your mathematical
model independently of specific parameter values and boundary conditions
and then simply import the mathematical model into specific
"experiments" which define the specific inputs and post processing you
wish to define. Generally I find it convenient to define different
levels of models for importing with more and more specifics set at each
level in order to make each model as reusable as possible.
David.
--
David Nickerson, PhD
Research Fellow
Division of Bioengineering
Faculty of Engineering
National University of Singapore
Email: [EMAIL PROTECTED]
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