Biology Reference
In-Depth Information
from a variety of databases, put it into a standard format, and
generate her own database with all the information the wet-lab
biologist needs.
Computational
: As part of the work for a paper he is writing,
Sam, a graduate student, needs to know the relative levels at
which a particular gene is expressed in different tissues of the
body. Sam organizes a collaboration with a nearby lab, which,
after some months, provides him with the data he needs, drawn
from experiments it has been doing on different cell lines. In the
meantime, Sam develops a theoretical model of gene expression
that he codes into an algorithm; it takes several days to run on
the computer cluster to which he has access through his lab.
When Sam receives the experimental data, he writes a differ-
ent program, fi rst to parse the data into a form he can work
with, and then to perform a series of statistical checks: he knows
he must be careful to control for differences between the ex-
periments and differences in overall expression levels. Sam now
has some results that he can compare with his own theoretical
model of gene expression. This comparison will form the basis
of a paper published in a well-respected biology journal.
The attitude toward “bioinformatics” expressed in the quotation
above suggests that there is a strong hierarchy implied in the distinction
between “bioinformatics” and “computational biology.” This attitude—
that data production is an unimportant sideshow to the real activity
of biology—was held by many (although not all) of my informants.
Moreover, this attitude has been internalized by many practicing bio-
informaticians, who see their roles as a “service” for biologists. During
my fi eldwork at the Broad Sequencing Center, the bioinformatics team
understood their role as providing “informatic support” for the core
work of the biologists in their labs. Although some resented the fact that
biologists would often demand that they dig up data or reorganize a
database at a moment's notice, they saw it as an inevitable part of their
day-to-day work in the laboratory. Like the stereotypical IT support
personnel in a large corporation, bioinformaticians saw themselves as
underappreciated and as playing an unacknowledged role in the success
of the work being done. Some others became disillusioned with their
“second-class” status: one of my interviewees had just quit his job at the
Broad because he felt that his skills were undervalued. He had found a
position at Google, where he felt that his expertise in informatics and
