Unsolved or Poorly Solved Computational Problems

Richard Scott rtscott at forgetspamPacbell.net
Fri Feb 28 04:57:45 EST 2003


Greetings Kevin,

Thank you for your thoughtful response. When I read it, I came to the
conclusion that my question was far too broad to be answered easily by
someone familiar with the actual details in the field. That might be
expected when I know so little. However, your response has provided me with
both starting points and an historical context into which I can put what I
already have investigated.

You brought up two points which are especially interesting because they
occur in many different fields. You stated that, "There are 'religious'
debates...(which of course depend mainly on how you define the problem you
are trying to solve)." Later, in the last paragraph, you defined "important"
problems as "..those that help answer biologically or medically important
questions". This focuses the issue on defining the term "biologically or
medically important". You also pointed out the dangers of incorrectly
abstracting the problem which would render the solutions "useless" in
answering the "underlying biological question".

Very insightful and potentially very fruitful observation. There is a short
book which you might find useful in this regard. It is The Art of Problem
Solving by Russell L. Ackoff, ISBN 0 471 04289-7. There is a paper backed
version available from Amazon and others with a different ISBN number.
Although someone might believe that your points are philosophical rather
than practical, my experience leads me to believe they could be the key to
real progress in this "new" field.

This leads to two other issues which I have encountered in both the academic
and commercial aspects of computer science, and which I suspect are big
problems in biotechnology. First, the lack of the right sort of experimental
data in key areas (e.g., actual disk accessing patterns on request by
request basis). Second, an unwillingness to design and construct tediously
accurate and complete simulation models (e.g., timing accurate disk
simulations).

The computer industry has no excuses for not properly instrumenting key
behavioral components in hardware but I imagine that a similar effort in
molecular chemistry or biology is virtually impossible with today's
technology. If that assumption is correct, there must be a crucial need for
accurate simulation capabilities to test various theories. In that regard, I
have looked at UCSD Professors Nathan Baker's and Michael J. Holst's work on
modeling the "MC", a simulation of the electrostatics of chained biological
molecular ( http://www.sciencenews.org/20010901/fob8ref.asp and
http://www.scicomp.ucsd.edu/~mholst/ ) and several of the gene sequencing
programs that are publically available (BLAST and so on). Still there seems
to be little or nothing available in terms of dynamically simulating actual
interactions. Also, the sequencing algorithms seem to be all statistical in
nature rather than trying to find exact or near exact matches. Is that the
result of the huge size of the problem, or performance considerations. What
happens if you might find more than one exact match? Some of these questions
are a result of sheer ignorance on my part for which I apologize but I
suspect there also issues of modeling inaccuracy and computational
intractability.

I have started to follow your suggestions regarding CASP experiments and
would appreciate any specifics you might have regarding the "thousands of
other problems in bioinformatics" particularly where the issues involve long
sequential chains of entities such as atoms, molecules or representations of
bases.

Richard Scott




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