Biology Reference
In-Depth Information
Our everyday familiarity with computers suggests that they are uni-
versal machines: we can use them to do the supermarket shopping,
run a business, or watch a movie. But understanding the effects of
computers—on biology at least—requires us to see these machines in
a different light. The early history of computers suggests that they were
not universal machines, but designed and adapted for particular kinds of
data-driven problems. When computers came to be deployed in biology
on a large scale, it was because these same kinds of problems became im-
portant in biology. Modes of thinking and working embedded in com-
putational hardware were carried over from one discipline to another.
The use of computers in biology—at least since the 1980s—has en-
tailed a shift toward problems involving statistics, probability, simula-
tion, and stochastic methods. Using computers has meant focusing on
the kinds of problems that computers are designed to solve. DNA, RNA,
and protein sequences proved particularly amenable to these kinds of
computations. The long strings of letters could be easily rendered as
data and managed and manipulated as such. Sequences could be treated
as patterns or codes that could be subjected to statistical and probabi-
listic analyses. They became objects ideally suited to the sorts of tools
that computers offered. Bioinformatics is not just using computers to
solve the same old biological problems; it marks a new way of thinking
about and doing biology in which large volumes of data play the central
role. Data-driven biology emerged because of the computer's history as
a data instrument.
The fi rst part of this chapter provides a history of early electronic
computers and their applications to biological problems before the
1980s. It pays special attention to the purposes for which computers
were built and the uses to which they were put: solving differential
equations, stochastic problems, and data management. These problems
infl uenced the design of the machines. Joseph November argues that be-
tween roughly 1955 and 1965, biology went from being an “exemplar
of systems that computers could not describe to exemplars of systems
that computers could indeed describe.”
1
The introduction of comput-
ers into the life sciences borrowed heavily from operations research. It
involved mathematizing aspects of biology in order to frame problems
in modeling and data management terms—the terms that computers
worked in.
2
Despite these adaptations, at the end of the 1970s, the com-
puter still lay largely outside mainstream biological research. For the
most part, it was an instrument ill-adapted to the practices and norms
of the biological laboratory.
3
The invention of DNA sequencing in the late 1970s did much to
