Biology Reference
In-Depth Information
puter brought with it epistemic and institutional reorganizations that
became known as bioinformatics. The sorts of problems and methods
that came to the fore were those that had been associated with comput-
ing since the 1950s: statistics, simulation, and data management.
As computing and bioinformatics grew in importance, physicists,
mathematicians, and computer scientists saw opportunities for deploy-
ing their own skills in biology. Physicists, in particular, perceived how
biological knowledge could be reshaped by methods from physics:
The essence of physics is to simplify, whereas molecular biol-
ogy strives to tease out the smallest details. . . . The two cul-
tures might have continued to drift apart, were it not for the
revolution in genomics. But thanks to a proliferation of high-
throughput techniques, molecular biologists now fi nd them-
selves wading through more DNA sequences and profi les of
gene expression and protein production than they know what
to do with. . . . Physicists believe that they can help, bringing a
strong background in theory and the modeling of complexity to
nudge the study of molecules and cells in a fresh direction.
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Where biology suddenly had to deal with large amounts of data, physi-
cists saw their opportunity. Physicists, mathematicians, and computer
scientists found myriad opportunities in biology because they had the
skills in statistics and data management that bioinformatics required.
Bioinformatics and the HGP entailed each other. Each drove the
other by enabling the production and synthesis of more and more data:
the production of bioinformatic tools to store and manage data allowed
more data to be produced more rapidly, driving bioinformatics to pro-
duce bigger and better tools. The HGP was Big Science and comput-
ers were tools appropriate for such a job—their design was ideal for
the data management problems presented by the growth of sequences.
Computers were already understood as suitable for solving the kinds of
problems the genome presented. Within this context of intensive data
production, bioinformatics became a special set of techniques and skills
for doing biology. Between the early 1980s and the early 2000s, the
management of biological data emerged as a distinct set of problems
with a distinct set of solutions.
Computers became plausible tools for doing biology because they
changed the questions that biologists were asking. They brought with
them new forms of knowledge production, many of them associated
with physics, that were explicitly suited to reducing and managing large
