Biology Reference
In-Depth Information
these are high-stakes issues for individual biologists as well as for the fu-
ture of biology as a whole. Just as mid-twentieth-century physics strug-
gled over its transformation to Big Science, biologists are struggling to
sort out their new institutional and epistemic roles. We have already
seen how the computational tools and methods described in chapter 1
posed challenges to older forms of biological work and knowledge. Dis-
agreements over tools, methods, and knowledge are still widely appar-
ent. Labels like “bioinformatics,” “computational biology,” and “sys-
tems biology” are important because they denote specifi c confi gurations
and hierarchies of knowledge, credit, and power within the biology
community.
1
The evidence I gathered from i eldwork and interviews suggests that
bioinformatics entails a reorientation of biological practices away from
“wet” biological material toward
data
. This may appear to be an obvi-
ous claim—
of course
computers deal with data. But what exactly are
data for the bioinformatician? Data are defi ned by the practices of using
the computer: they are the stuff that computers manipulate and operate
on. They cannot be understood apart from the computer and have no
meaning outside of a digital context. The masses of raw, complicated,
undigested, disordered stuff that are produced by instruments and
experiments become data as they enter and fl ow through computers.
Without computers, they would have no use or signifi cance.
2
So using
computers is by defi nition a data-driven practice.
However, the consequences of this reorientation toward data are
more complicated. The data corresponding to an object never consti-
tute a perfect copy of that object. For instance, the data representing
a genome are not the same as the “wet” molecular DNA that you fi nd
inside your body. But at the same time, it is impossible to conceive of a
genome outside a computational context. The work of sequencing and
assembling it would have been (and remains) unimaginable without a
computer. Even if this somehow could have been achieved, the effort
would have been useless without the ability to share and access the data
that computers provide. Even the molecular DNA from your body is
conceived in terms of its computational or data representation.
To say that biology is becoming about data, then, is to say that it is
tied to all sorts of practices, structures, and constraints associated with
hardware and software. This claim invites us to investigate how those
data are made and used. It suggests that bioinformatics is a distinct and
competing set of practices and knowledge for biological work. These
practices—derived from computing practices in physics—reorient bio-
informatics toward particular sets of questions that are distinct from
