Biology Reference
In-Depth Information
engaged in a dialectic in which each drives the other: the valorization
of mass, volume, and speed lead to a greater demand for data, which
justifi es better and faster sequencing, which, in turn, contributes to the
continued success of the “quantitative” approaches.
Michael Fortun has drawn attention to the cultures of “accelera-
tion” and “speed” that surrounded the Human Genome Project. He
argues that much of the controversy surrounding the project was con-
nected to its speed—many wondered why the HGP was considered to
be so urgent. The commitment to the HGP involved a commitment to
prioritizing (and therefore speeding up) certain kinds of biological work
in particular labs.
21
Bioinformatics has become the space in which the
confl ict between these older and newer (slower and faster) forms of
practice ultimately plays out. Already by the mid-1980s, “informatics
was becoming the most important speed nexus”;
22
computers were cru-
cial for the HGP not only to achieve automation, but also to manage
and maintain the speed of data production.
23
The continued drive to-
ward rapid and large-scale biology was created not by the HGP, but by
computers.
More data create not just more knowledge, but a qualitatively dif-
ferent kind of knowledge. Consider, for example, the type of scientifi c
publication routinely produced by the Broad Institute. In 2005, the lab
published a paper based on a draft of the chimpanzee (
Pan troglodytes
)
genome. The sequencing work alone—performed at both the Broad and
the Washington University School of Medicine—was not considered
publishable material in and of itself. Indeed, the chimpanzee sequence
had been uploaded to public databases as it was completed and had
been available for some time. Rather, the “chimpanzee genome paper”
consisted largely of analysis and comparative work performed
on
the
sequence itself. The work of the Broad team consisted of building soft-
ware, aligning the sequence, and statistically analyzing the data. The
result was a high-level overview of the features of the chimpanzee se-
quence. This published knowledge is not raw data, nor is it anything
like detailed analysis of a particular gene or cell or protein; rather, it is
an attempt to fully characterize the genome of an organism at a high
level.
The Broad's techniques aim to understand the genome in its totality—
to draw conclusions about all genes, or all transposons, or all repeating
elements in a genome. Software and statistics generate a high through-
put of knowledge, an effi cient transformation of data into publications.
Those at the Broad who were involved in this work related how they
thought that computers had changed the questions that were asked in
