Hi folks,
Pretty interesting read. I actually came to what I do now through a
heavy cellular neurosci background so this disconnect between systems
biology and neurosci is something that has really bugged me. They
mention in the paper that SBML doesn't provide the spatial support
needed for it to be useful to computational neuroscientists. CellML with
its emphasis on multiscalar integration and modularity along with
FieldML to describe the geometric information could address these issues.
Also, I'm always interested in how CellML is represented in these kinds
of publications. It is usually seen (as in this paper,) by systems
biologists as a competing language for describing systems biology, which
is understandable but only partly true. I think we need to seriously
market CellML as a Physiome language, a lot more than we do. This will
be a topic in the upcoming paper about the CellML repository I'm
starting to put together - that is: the name of the software is Physiome
Model Repository 2 - what has it got to do with the Physiome Project then?
Kind regards,
James
David Nickerson wrote:
Why Are Computational Neuroscience and Systems Biology So Separate?
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000078
some interesting comments, although not totally accurate...
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