On Mar 30, 2009, at 8:15 AM, Oliver Ruebenacker wrote:
Hello Pat, All,
On Sun, Mar 29, 2009 at 11:23 PM, Pat Hayes <pha...@ihmc.us> wrote:
On Mar 29, 2009, at 10:48 AM, Oliver Ruebenacker wrote:
Perhaps the question should read: What would you advice to some one
who wants to build an ontology to describe pathways for Systems
Biology purposes?
I really have no advice to give, as I know virtually nothing about
systems
biology. My remarks were based on your raising the topic of
statistical
ensembles, which is enough to make me want to go and do something
else, I'm
afraid.
There is no reason to be scared of statistical ensembles!
Pat Hayes isn't scared of them, but PatHayes the ontologist is very
leery of trying to describe them using ontologies written in any logic-
based language. We don't (yet, AFAIK) have a satisfactory ontology for
things like variances and expectations and probabilities. None of this
has been adequately formalized yet, and this whole area is a logical
minefield: for example, reasoning about approximate values is a well-
known problem area, rife with potential "paradoxes" like the heap
argument.
Forget for the moment about Systems Biology and think of Science in
general.
A scientist applies a method to obtain results. Talking about the
method means talking about things particular to the discipline and the
tools used (e.g "On March 14, I placed the soccer ball on my table and
held my yellow ruler next to it.").
The results can also be expressed in this language (e.g. "My yellow
ruler read 27.3 inches when held next to the soccer ball on my
table"), which is useful for those interested in the method, but it is
not required for those only interested in the results. In fact, if we
want to collect, combine and compare results obtained by different
methods, details particular to methods are usually counter-productive
(ruler? measuring tape? caliper? laser? red? yellow? table? chair?).
The consumer of the results is typically interested in a statement
such as "the diameter of a soccer ball is 27.4 inches plus-minus 0.3
inches". An expectation value and a variance.
But what does the "diameter of 27.4 inches plus-minus 0.3 inches" in
above statement inhere in? Certainly not one particular soccer ball.
How about the set of all the soccer balls in the world? But why would
we be interested in all the soccer balls in the world?
Because you want to make _general_ statements about soccer balls. That
"general" is another way of saying "All ... in the world". And general
statements are what ontologies largely consist of.
What if in some
strange place, people produce soccer balls of unusual sizes, would
that change the result for us?
If they really were soccer balls, yes. But you could always invent a
new category of "strange balls similar to soccer balls".
What we really mean when we say that a soccer ball has a diameter of
such and such, is that we imply that there are standard ways to obtain
soccer balls (e.g. going to the next sports store and buying one, or
taking one from the equipment room of the next gym, or participating
in a soccer match), and that these ways are equivalent in the expected
results.
Hmm. That is not what I mean when I say that. What I mean is, all
soccer balls have a diameter of such and such. I don't accept the
premis that all statements are reducible to statements about
experimental scenarios (even in science, although I will grant you
that this is more plausible for quantum-theoretical physics, if one
accepts the Copenhagen interpretation. I prefer the transactional
interpretation, myself.)
So there will be a range of possible scenarios (e.g. a soccer
ball of 27.2 inches, a soccer ball of 27.342 inches, a soccer ball of
9*pi inches, etc.) and each outcome comes with a probability. These
probabilities are usually not all the same, and since the number of
possible scenarios is typically infinite, it makes no sense to assume
they are. The probability distribution over the set of possible
outcomes is a ensemble.
Yes, I know. I also know that I have absolutely no idea how to
adequately formalize this so that its salient properties can be
deduced from the formalization. I also, BTW, have strong doubts that
this is the best framework within which to attempt to formalize
biological information, but no doubt we would have to agree to
disagree on that point.
Pat
Enter Systems Biology. Systems Biology is a consumer of results from
many disciplines. Its objective is to put together results obtained by
a wide range of experimental, theoretical and computational methods in
Biological Physics, Molecular Biology, Physical Chemistry,
Biochemistry, Computer Science and Applied Math. Some of these methods
involve tracking single molecules, of definite sets of molecules. Some
do not. so Systems Biology needs a language to talk about these
results without referring to artefacts of methods used, which is the
language of ensembles.
Take care
Oliver
--
Oliver Ruebenacker, Computational Cell Biologist
BioPAX Integration at Virtual Cell (http://vcell.org/biopax)
Center for Cell Analysis and Modeling
http://www.oliver.curiousworld.org
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