Biology Reference
In-Depth Information
informaticians have replaced this linear approach with tools that search
for patterns in large volumes of data. They are generating knowledge
out of the seeming randomness and disorder of genomes.
When computers were brought into biology in the 1980s, they
brought with them certain patterns of use, certain practices, particular
algorithms, and modes of use that persisted in biological work. It was
not that the machines themselves dictated how they were to be used, or
the kind of biology that could be practiced with them, but rather that
their users had established ways of working and well-known ways of
solving problems that could and would be deployed in organizing and
analyzing biological data. These ways of working have confl icted with
and challenged older forms of doing and knowing in biology.
This confl ict has arisen partly because the shift between old and new
has not been merely a technological one. Bacon's vision of science ex-
tended to a rigidly structured society, working toward the pursuit of
knowledge through a strict division of labor. One group of individu-
als would collect data, conducting a large and diverse range of experi-
ments; a second group would compile the results of these experiments
into tables; and a third would construct theories based on these tabu-
lated observations.
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This chapter has shown that hypothesis-free biol-
ogy is not merely about a shifting epistemological approach to scientifi c
inquiry—rather, it is entailed by and intertwined with changes in tech-
nologies, changes in disciplinary boundaries, changes in institutions,
changes in the distribution of funding, and changes in the organization
of work and workers. In other words, Bacon was right in suspecting
that the production of a particular kind of knowledge required a par-
ticular organization of people and spaces.
In chapters 3 and 4 we will see how bioinformatics has driven just
these kinds of shifts in the organization of biological work. The emer-
gence of bioinformatics meant the emergence of data in biology. Data
cannot be understood separately from computers and the ways in which
they are used: they entail the asking of specifi c sorts of questions and
enable particular sorts of solutions. Data are not like a specimen or a
paper trace—they move around in virtual space and enter into digital
relationships that are specii c to the computer. The rest of this topic is
devoted to showing precisely how data are constrained by the physical
and virtual structures that create and store them.
