ILLUSTRATIVE PROBLEM DOMAINS AT THE INTERFACE OF COMPUTING AND BIOLOGY 299
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9
Illustrative Problem Domains at the
Interface of Computing and Biology
9.1 Why Problem-focused Research?
Problems offered by nature do not respect disciplinary boundaries. That is, nature does not package
a problem as a “biology” problem, a “computing” problem, or a “physics” problem. Many disciplines
may have helpful insights to offer or useful techniques to apply to a given problem, and to the extent
that problem-focused research can bring together practitioners of different disciplines to work on shared
problems, this can only be a good thing.
This chapter describes problem domains in which the expenditure of serious intellectual effort can
reasonably be expected to generate (or to require!) significant new knowledge in biology and/or com-
puting. Biological insight could take different forms—the ability to make new predictions, the under-
standing of some biological mechanism, the construction of a new biological organism. The same is true
for computing—insight might take the form of a new biologically inspired approach to some computing
problem, different hardware, or novel architecture. It is important to note that these domains contain
very difficult problems—and it is unrealistic to expect major progress in a short time.
Challenge problems can often be found in interesting problem domains. A “challenge problem” is
a scientific challenge focused on a particular intellectual goal or application (Box 9.1). Such problems
have a long history of stimulating important research efforts, and a list of “grand challenges” in compu-
tational biology originating with David Searls, senior vice president of Worldwide Bioinformatics for
GlaxoSmithKline, includes protein structure prediction, homology search, multiple alignment and phy-
logeny construction, genomic sequence analysis, and gene finding.^1 Appendix B provides a sampling of
grand challenge problems found in other reports and from other life scientists.
The remainder of this chapter illustrates problem domains that display the intertwined themes of
understanding biological complexity and enabling a novel generation of computing and information
science. It incorporates many of the dimensions of the basic knowledge sought by each field and
discusses some of the technical and biological hurdles that must be overcome to make progress. How-
ever, no claim whatsoever is made that these problems exhaust the possible interesting or legitimate
domains at the BioComp interface.
(^1) D.B. Searls, “Grand Challenges in Computational Biology,” Computational Methods in Molecular Biology, S.L. Salzberg, D.
Searls, and S. Kasif, eds., Elsevier Science, 1999.