in the News
by Bert Weinstein
World's Most Accurate Lathe
Attack on Cancer
Memory Goes High Rise
Biology and Biotechnology Research Program
BIOLOGICAL scientists are
beginning to reap the benefits of integrating high-performance computing
with laboratory research. Work in Lawrence Livermore's Biology and
Biotechnology Research Program is bringing computer modeling into
the same essential role in bioscience that it plays in physics and
engineering. Every complex physics experiment uses computer models
to help design the experiment, guide its construction, predict the
outcome, and suggest modifications. Every large engineering project,
such as building an automobile, bridge, or integrated circuit, uses
computational modeling to explore alternatives, optimize designs,
and recognize flaws.
Over the past century, bioscience
has evolved from a qualitative, observational discipline to a quantitative,
predictive science. Molecular biology and genetics are generating
vast amounts of complex data, and the generation rate is accelerating.
Given the amount of information, more and more bioscientists recognize
the need for large-scale computational tools. At the least, researchers
need computers to collect, store, organize, and display their data
and increasingly are using computers to accurately model the complex
processes they are studying.
Throughout its history, the
Laboratory has pioneered the use of powerful computers to solve
complex scientific problems. The best known example is the extraordinarily
complex modeling of nuclear detonations. At first glance, modeling
nuclear weapons and modeling biological processes would seem to
have little, if anything, in common. In truth, they are surprisingly
similar. In both, many complex processes and variables work together
to produce an end result with only a few measurable quantities,
which are often averages spanning the entire experiment. Diagnostics
are few—many of the most interesting quantities cannot be
observed directly or take place on extremely brief time scales.
Individual experiments are expensive and/or time consuming, so only
a few can be conducted—not nearly enough to explore all the alternatives.
Modeling has many values.
It fills the gaps in sparse experimental data, gives researchers
insights into intermediate processes that cannot be directly observed,
and allows many more virtual computer experiments than actual physical
experiments. Computer models also force scientists to make sense
of all available data at once, not just in piecemeal fashion. By
integrating disparate bits of data, models inevitably provide insight
into a problem.
As described in the article
entitled A New Kind of Biological Research,
advanced computation permits bioscientists to really "see" inside
biochemical processes in breathtaking detail and learn how reactions
take place. Modeling occurs at several levels of resolution. It
can simulate the behavior of a few hundred atoms—for example, a
few base pairs of DNA—with full quantum mechanical resolution. Or
it can reveal the workings of larger systems with more abstraction
and less precision. For example, the three-dimensional folding of
a long chain of amino acids into a working protein is modeled partly
from its physical and chemical properties and partly by comparing
the sequence with known "folds"—structural patterns that are components
of other functional proteins.
As in the physical and engineering
sciences, confidence in biochemical computational models is developed
by constantly testing them against experimental data obtained by
biologists and biochemists working closely with computational experts.
As the models are found to accurately predict measurable quantities,
they begin to be trusted and relied on to guide experiments and
to raise questions that suggest productive new lines of research.
Today, Lawrence Livermore
scientists are at the forefront of integrating computation and experiment
in bioscience. The challenge is to improve modeling accuracy and
extend biosimulations to higher levels of complexity—for example,
to groups of proteins working together to repair damaged DNA and,
beyond, to intracellular components, structures, and communication
paths. These research dreams extend to someday modeling the workings
of an entire cell. The quest will, indeed, be an exciting one.
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