Unsolved or Poorly Solved Computational Problems

Kevin Karplus karplus at bray.cse.ucsc.edu
Thu Feb 27 10:01:55 EST 2003

In article <GMy5a.1151$d32.49293459 at newssvr14.news.prodigy.com>, 
	Richard Scott wrote:
> What are the major unsolved or poorly solved computational problems in
> computational biology that could potentially lead to real improvements in
> people's health and welfare?  I know this is a naive question but my
> knowledge is rudimentary, and I don't know where to find a description of
> the problems or the potential solutions.

> I have been surfing the Web to find answers but some issues are unclear.
> For example, is the sequencing problem solved to everyone's satisfaction?
> What kinds of models and algorithmic approaches are being used for protein
> folding?  What are the important (not just interesting) problems?

Protein folding is far from solved---there are books and conferences
dedicated to this problem.  There are "religious" debates between
biophysicists and bioinformaticians about whether particular
techniques are helping advance the field (which of course depend
mainly on how you define the problem you are trying to solve).
I would recommend the special issues of Proteins: Structure, Function,
and Genetics dedicated to the results of the CASP experiments as a
good source of information about the field.

There are thousands of other problems in bioinformatics.  In many
cases, the solution is easy once the right question is asked (that's
one of the great things about a new field).  In other cases, decades
of work have already been put into finding solutions, some of which
are still only marginally usable.  As our understanding of biology
increases and our data grows, we often find that solutions that were
perfectly adequate in the past are no longer useful, and new tools and
mthods are needed.

"Important" problems are those that help answer biologically or
medically important questions.  Abstracting away from the biology is
often tricky, as assumptions get built into the problem statement that
may make solutions useless for the underlying biological question.

Kevin Karplus 	karplus at soe.ucsc.edu	http://www.soe.ucsc.edu/~karplus
life member (LAB, Adventure Cycling, American Youth Hostels)
Effective Cycling Instructor #218-ck (lapsed)
Professor of Computer Engineering, University of California, Santa Cruz
Undergraduate and Graduate Director, Bioinformatics
Affiliations for identification only.

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