Biology Reference
In-Depth Information
gists are increasingly called on to justify their skills and expertise within
a diverse landscape of practices and ways of knowing. In particular, biol-
ogists have needed to face the challenge mounted by computer scientists
who have turned their attention to the analysis of biological problems.
This challenge is not just an issue of communication or language, but a
struggle over whose modes of doing and knowing will persist in biology.
The stakes in this battle are high: jobs, credit, and money are on
line. Will, a veteran of the HGP, told me that when the Whitehead Insti-
tute began to scale up for human genome sequencing, it stopped hiring
people with degrees in biology and started hiring people with degrees
in engineering and experience with management.
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The director of the
Broad Institute, Eric Lander, is a former business school professor with
a PhD in mathematics; he has received many accolades for his work
on the HGP and is seen as one of the visionaries of the fi eld. Biologists
are just getting used to publishing papers in which their names might
appear alongside those of a hundred other individuals, including peo-
ple without degrees in biology.
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The ideal-typical biologist of the old
school—making a contribution to knowledge through toil in his labora-
tory with only his test tubes and his bacteria to keep him company—is
under threat. The use of the term “bioinformatics” by some biologists
as a pejorative refl ects a discomfort with new forms of biological prac-
tice that are massively collaborative: the fact that computers are used is
secondary to the fact that they are used to facilitate the collection, dis-
tribution, and sharing of information among a wider and wider group
of non-biologically trained individuals.
One way in which biologists defend traditional forms of practice is
to question the extent to which computational methods can gain access
to nature. Computation is all well and good, they argue, but it requires
data from “real” experiments, and any conclusions it reaches must ul-
timately stand up to tests in the wet lab. Without denying the potential
power of computational methods for biology, these biologists maintain
a hierarchy in which the wet lab becomes the defi nitive source of au-
thority. The attitude of Charles DeLisi is typical: “You have to prove it
in the lab, whatever comes out. . . . So, a computer is useful to generate
a kind of hypothesis, . . . biology is, like the physical sciences, strictly
empirical, we want observational evidence for proof.”
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Others are quick
to criticize work that lacks a sensitivity to wet biology:
The problem is when the “bio” is missing from informatics. An
awful lot of people come from computer science into this fi eld
