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                            Programs from the past

[A Chaotic Attractor] [1]Rooting around in the mustier corners of my
harddrive, I came across this program I had written nearly a decade ago while
attending FAU (Florida Atlantic University) [2]. At the time, I was a
Computer Science [3] major, working in the Math Department [4] for two Ph.
D.s, one out of the Psychology Department [5] and one from the Center for
Complex Systems [6], both of which were studying biophysics.

Not that I understood anything of what they actually did; all I did (besides
keeping a few computers up and running) was write programs to their
specifications.

The program I found was one of three I wrote dealing with a pair of equations
they were studying:

x = ((A × y) + B) × x × (1 - x)
y = ((C × x) + D) × y × (1 - y)

From what little I remember, I seem to recall this being a form of simulation
of two neurons interacting, but I have no idea how to interpret the results;
all I know is that it can produce some rather striking images by ploting the
results, then feeding those back into the equation, repeating this several
thousand times. By changing the constants A, B, C and D you get wildly
different results.

This program was had four slider controls that allowed to you vary the
constants and updated the result in real time (and was quite impressive to
view on the SGI workstation on my desk at school). The second one (written
for a particular video card on a PC) would randomly pick A, B, C and D; you
could view the previous 16 images and blow any of them up (or save the
parameters to disk for later viewing). You could also have it step
sequentially through values. This program was actually the backdrop for a BBC
(British Broadcasting Company) [7] interview of one of the doctors I was
working for.

The third program I wrote was a bit more complex. Instead of plotting the
results of interation through the equations, it instead kept track of the
results, and when it detected a loop, it would then save the number of points
generated before a loop was detected (some values of A, B, C and D would
vasillate between two or three points, while other values of A, B, C and D
would never repeat even after 5,000 interations). And it worked its way
systematically, varying A through its range of values and keeping B, C and D
constant. It would then bump B up, and then run through all values of A, then
bump B up, and so on until B hit its upper limit, then bump C up a bit, and
so on. It took the better part of a year to run through all values of A, B
and C. Then the data was plotted in three dimentions, using time as one of
the dimentions (basically, an animation of a rather odd looking two
dimentional image) and stored on video tape (which took me the better part of
three days making, having to edit about five minutes of video frame-by-
frame).

Again, not that I understood what the results where, just that I did it.

I enjoyed the work, and the office space [8] was incredible; there are days
when I wish I was still in that office.

Sigh.

Just for a lark, I decided to Google [9] for the doctors I worked for and
came across some of their recent work:

> A new proprietary de novo peptide design technique generated ten 15-
> residue peptides targeting and containing the leading nontransmembrane
> hydrophobic autocorrelation wavelengths, “modes”, of the human m muscarinic
> cholinergic receptor, mAChR. These modes were also shared by the mAChR
> subtype (but not the m, m, or m subtypes) and the three- finger snake
> toxins that pseudoirreversibly bind mAChR. The linear decomposition of the
> hydrophobically transformed mAChR amino acid sequence yielded ordered
> eigenvectors of orthogonal hydrophobic variational patterns. The weighted
> sum of two eigenvectors formed the peptide design template. Amino acids
> were iteratively assigned to template positions randomly, within
> hydrophobic groups. One peptide demonstrated significant functional
> indirect agonist activity, and five produced significant positive
> allosteric modulation of atropine-reversible, direct- agonist-induced
> cellular activation in stably mAChR-transfected Chinese hamster ovary
> cells, reflected in integrated extracellular acidification responses. The
> peptide positive allosteric ligands produced left-shifts and peptide
> concentration-response augmentation in integrated extracellular
> acidification response asymptotic sigmoidal functions and concentration-
> response behavior in Hill number indices of positive cooperativity. Peptide
> mode specificity was suggested by negative crossover experiments with human
> mACh and D dopamine receptors. Morlet wavelet transformation of the leading
> eigenvector- derived, mAChR eigenfunctions locates seven hydrophobic
> transmembrane segments and suggests possible extracellular loop locations
> for the peptide-receptor mode-matched, modulatory hydrophobic aggregation
> sites.
>

“Designing Human m Muscarinic Receptor-Targeted Hydrophobic Eigenmode Matched
Peptides as Functional Modulators [10]”

Yea, I don't understand it either.

And that's just the abstract. I can't imagine how impenatrable the actual
paper is.

[1] gopher://gopher.conman.org/gPhlog:2004/06/09/attractor.gif
[2] http://www.fau.edu/
[3] http://www.cse.fau.edu/
[4] http://www.math.fau.edu/
[5] http://www.science.fau.edu/psychology/default.html
[6] http://www.ccs.fau.edu/
[7] http://www.bbc.co.uk/
[8] gopher://gopher.conman.org/0Phlog:2002/03/04.2
[9] http://www.google.com/
[10] http://www.biophysj.org/cgi/content/abstract/86/3/1308

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