Re: Math and bio?

On Dec 28, 5:34 pm, Jeswin <phillyj...@gmail.com> wrote:
> I didn't read all the links above yet but I was hoping there was a
> good wikipedia entry on Rule-based modeling. I found an intro with
> Agent-based modeling. I think they are the same thing.

I wish there was a page too! We should do one. But, yes you are right
it is close to agent-based modeling. Our agents have sites, which may
have internal states, typically used to denote phosphorylation and
other post-translational modifications, and may also bind to other
sites,
to represent the formation of complexes. Rules describe conditions for
agents
to associate, dissociate or get modified. Agent deletion or creation is
also possible.
You can model a substantial part of the mechanistic interactions
involved
in signalling using this kind of language. Models are typically easier
to
write and modify than the ones based on reactions. Some extensions
takes care of the modeling of spatial constraints and/or spatiallly
heterogeneous
systems.

If you want you can read this 1 page article
on rule-based and when to use it:
http://www.nature.com/nmeth/journal/v8/n2/full/nmeth0211-130.html

for a slightly longer intro and a concrete example, check this:
http://www.pps.jussieu.fr/~danos/pdf/eov.pdf

> Anyway, could I use one of these programs to do simple modeling like
> how immune system function, organic chemical synthesis or other stuff
> you find in textbooks?

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> On Sat, Dec 24, 2011 at 8:01 AM, Vincent Danos <vincent.da...@gmail.com> wrote:
> > 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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