Re: Math and bio?

Hi

In the same rule-based family, that is indeed very useful for
combinatorial systems, there is also Kappa
(http://kappalanguage.org, http://groups.google.com/group/kappa-users).

The best model prize at iGEM'10 (see their model here:
http://homepages.inf.ed.ac.uk/s0458094/CS2Bio11/)
and '11 went to Edinburgh teams which were using an ad hoc spatial
extension of
Kappa (spatial Kappa: http://www.demonsoft.org/SpatialKappa/).
Differently than coupling with Smoldyn,
in spatial Kappa, you can execute rule-based in space without
translating to ordinary reactions (of which there are
typically too many to go the translation way).

For your specific context, ie synaptic plasticity via transcriptional
regulation of receptor populations in
the post-synaptic density (PSD), depending on what scales and details
you want to incorporate to the model,
you will end up using vastly different tools.

I am not a PSD expert, but it seems a key issue is the level of
granularity you choose for describing Ca2+ signalling;
there will be local concentrations of Ca2+ pairing with kinases fixed
to the PSD and modifying the properties
of other receptors in the neighbourhood. If you want to represent that
(obviously a smaller time scale than
transcription), then you need to map PSD in space and run a coupled
model of ca2+ diffusion. Another issue
is whether to represent the dynamic assembly of the PSD itself, and
how realistic this assembly model should be
(I think we know now that receptors sort themselves in a circular way
and depending on their types live closer or further
from the center of the synpatic contact).

This article could be a good starting point to contemplate the rule-
based option for
a detailed model including some stylized version of PSD assembly:
http://pubs.rsc.org/en/content/articlelanding/2011/mb/c1mb05152k

For a higher-level view of synaptic plasticity, see references on this
page:
http://homepages.inf.ed.ac.uk/s0677281/Main.html

Cheers
Vincent

On Dec 23, 4:12 pm, Keith Callenberg <keithcallenb...@gmail.com>
wrote:
> It's not clear to me what kind of model you are looking for, but there
> are two software packages that I think would be worth checking out.
> BioNetGen (http://bionetgen.org/) is a powerful system for rule-based
> modeling that allows you to write general rules that propagate into
> many reactions. It can be paired with Smoldyn (http://www.smoldyn.org/) to stochastically model the spatial dependence of
> these reactions.
>
> Keith Callenberg
>
> On Dec 22, 2:18 pm, Nathan McCorkle <nmz...@gmail.com> wrote:
>
>
>
>
>
>
>
> > Quick comment, I know a lot of calculations for enzyme kinetics are based
> > with the rate of diffusion being the limit... then you'd probably need info
> > about protein localization... are they in vesicles or free-floating or
> > membrane attached
>
> > I will keep this in mind and try to dig something up
>
> > Sent from my mobile Android device, please excuse any typographical errors.
> > On Dec 22, 2011 9:20 AM, "Jonathan Nesser" <jonathan.nes...@gmail.com>
> > wrote:
>
> > > I've been getting into mathematical models lately, and have noticed
> > > that many of these models don't really take into account the signaling
> > > complexities of biology. To this end I was wondering if anyone could
> > > point me in the direction of a general equation, etc. that models
> > > either the process of selecting a gene to be transcribed in a cell
> > > (all of the different transcription affinity and negating factors), or
> > > of quantifying the amount of mobilization of an enzyme which is
> > > activated through a complex enzyme cascade. A name of an equation or
> > > modeling style would be enough to get me started, I haven't been able
> > > to find much of anything beyond the idea of the stochastic general
> > > equation and markov, non-markov type equations. To put a context to
> > > this broad question, I'm interested in the ligand gated g protein
> > > receptor cascades in neurons, and the control of receptor populations/
> > > synapse modulation (synaptic placticity) at a genetic (or at any
> > > other) level. Having looked over a goodly amount of articles it seems
> > > to me like this has been mainly studied at a qualitative level, much
> > > less so at a specific quantitative level. Sorry to pollute the board
> > > with my neuroscience again :P, but I think this would be interesting
> > > to the slightly higher level genetics researchers here as well. :)
> > > Thanks for any information in advance, and I apologize for my
> > > ignorance if this is a commonly understood topic, I don't really have
> > > access to a professor of, well, anything. :)
>
> > > Jonathan Nesser
> > > diybioandneurosci.blogspot.com
>
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