I haven't seen any posts for a couple of days. Is the list just quiet or has my ISP once again starting filtering out messages from lists?
This note from Nature on-line today seems to have some relevance to the modelling and simulation studies of PCT structure possibilities. They compared millions of potential structures with a wide range of parameter values. I've spent months looking at just three or four structures to model the sleep studies. Obviously there are algorithmic ways to do this experimental anipulation. Perhaps someone on the list is enough of a programmer to be able to use some related approach.
---------------Nature article follows-------------
Nature 450, 5 (1 November 2007) | doi:10.1038/450005a; Published online
31 October 2007
James E. Ferrell
A systems biologist encourages modelling by the millions.
In a typical modelling study, we write down equations, solve them, and
see whether they account for known data. If they do, we claim to
understand some bit of biology. One huge caveat is that many other
models might have matched the data just as well.
Researchers from Peking University in Beijing and the University of
California, San Francisco, have devised a satisfying way of dealing with
this problem (W. Ma et al. Mol. Syst. Biol.2, 70; 2006).
Their starting point was epithelial patterning in the fruitfly
Drosophila. During embryogenesis, a system known as the 'segment
polarity network' generates repeating stripes of gene expression. The
stripes are initially fuzzy and later become sharp. Ma et al. set out to
see what simple gene circuits were best suited to this sharpening
They formulated differential-equation models for about 14 million ways
of connecting two or three segmentation genes, then randomly chose 100
sets of parameters that defined the strength of the interactions for
each gene. They then carried out computations for each combination to
determine which of them converted fuzzy stripes into sharp ones.
Many topologies worked for at least one parameter set. But only a
fraction worked for more than one or two. Interestingly, the most robust
topologies were all variations on the same design - each had three
sub-circuits, one 'stripe generator' motif and two bistable 'response
sharpeners'. These findings give hope that complex networks may be
decomposed into modular sub-circuits with understandable functions.
Comprehensively examining millions of models is a lot of work, but is
not impossible. And, as Ma et al. show, it can yield important insight
that could not have been derived from studies of one or two.