Hi Peter,
I guess I framed it as a question to the community, but it was more of a
leading question that I'd like to address in the paper on the
repository. What I'm really talking about is the common preconception
that SBML and CellML are designed to fill the same niches. The niches
overlap but are not the same; I see the idea of CellML as part of the
Physiome Project as being quite a powerful way of explaining its niche.
With respect to the existence of multiple standards, I would go even
further: it is essential to have more than one standard for representing
this kind of information, lest the standard define the field, rather
than the field defining the standard.
Cheers,
James Lawson
Peter Hunter wrote:
Hi James,
Re your final question - the Physiome Project at the moment is largely
about (i) the development of the markup languages CellML and FieldML
(& maybe ModelML for the physics) and their associated model
repositories and software tools, and (ii) strategies for bridging
spatial and temporal scales. I see no reason at all not to include
neuroscience in this picture - in fact there are a number of
initiatives relating to a 'brain physiome' just getting underway. The
essence of the Physiome is the recognition of the need to link models
of structure and function across spatial scales from nm to m and
temporal scales from brownian motion to human lifetime turnover of
proteins. Easy to say ...
While CellML and SBML are in some way competing standards, both
communities are helping one another greatly by promoting the idea of
modelling standards .. and provided we can convert between them,
there's no particular disadvantage in having two standards.
Cheers,
Peter
James Lawson wrote:
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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