In Hunter, L. (Ed.), Artificial Intelligence in Molecular Biology, AAAI Press, Menlo Park, CA.1993, pp. 225-233.
Department of
Biochemistry & the Section
on Medical Informatics, Stanford
University School of Medicine, Stanford,
California 94305-5307.
Our understanding of any process can be measured by the extent to
which a simulation we create mimics the real behavior of that
process. Deviations of a simulation indicate either limitations or
errors in our knowledge. In addition, these observed differences
often suggest verifiable experimental hypotheses to extend our
knowledge.
The biochemical approach to understanding biological processes is
essentially one of simulation. A biochemist typically prepares a
cell-free extract that can mediate a well-described physiological
process. The extract is then fractionated to purify the components
that catalyze individual reactions. Finally, the physiological
process is reconstituted in vitro. The success of the biochemical
approach is usually measured by how closely the reconstituted process
matches physiological observations.
An automated simulation of metabolism can play a role analogous to
that of the biochemist in using and extending knowledge. By carefully
representing the principles and logic used for reasoning in the
laboratory, we can simulate faithfully, on a computer, known
biochemical behavior. The simulation can also serve as an interactive
modeling tool for reasoning about metabolism in the design of
experiments, in discovery, and in education.
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