CULTURE AND RESEARCH INFRASTRUCTURE 367
and relies on the ability to sift through and recognize patterns in large volumes of data whose meaning can
then be inferred. Of course, predictions that emerge from the analysis of large volumes of data must still
be verified one at a time, and science is today far from the point at which such analysis would, by itself,
provide reliable biological conclusions. Nevertheless, such analysis can play an important role in suggest-
ing interesting hypotheses and thus expand the options available for biological exploration.
10.3.1.5 A Caricature of Intellectual Differences
A number of one-liners that can be used to encapsulate the differences described above, though as
with all one-liners, there is considerable oversimplification. Here are four:
- The goal of computer science (CS) is to develop solutions that can be useful in solving many
problems, while the goal of biology is to look for solutions to individual and specific problems. - Computer science is driven by the development of method and technique, while biology is
driven by experiment and data. - Computer scientists are trained to search for boundary conditions and constraints, whereas
biologists are trained to seek signal in the noise of their experimental data. - Computer scientists are trained to take categorical statements literally, whereas biologists use
them informally.
10.3.2 Differences in Culture
Another barrier at the BioComp interface is cultural. Each field has its own cultural style, and what
seems obvious to practitioners in one field may not be obvious to those in the other. Consider, for
example, differences between computer science and biology. Before PowerPoint became ubiquitous to
both fields, computer scientists tended to use overhead transparencies in visiting lectures, while biolo-
gists tended to use 35 mm slides. Computer science, as a discipline, can often be pursued while working
at home, whereas biological lab work requires being “in the office” to a far greater extent—a computer
scientist who is away from the lab may well be seen by biologists as “not being around enough” or “not
being a team player.” Computer scientists are accustomed to having their own office space, while
biologists (especially postdoctoral associates) work out of their labs and rarely have their own offices
until they achieve an appropriate seniority.
Such differences are in some sense trivial, but they do suggest the reality of different cultures, and it is
helpful to explore some other differences that are not so trivial. One of the most important differences is that
of intellectual style: the discussion in Section 10.3.1 would suggest that biologists (especially those untrained
in quantitative sciences) may well distrust the facile approaches and oversimplified models of computer
scientists or mathematicians unfamiliar with the complexities of living things, and the computer scientist
may well regard the biologist as obsessed with details and molecular parts lists rather than the qualitative or
quantitative whole. This section explores some issues that lie outside the domain of intellectual style.
10.3.2.1 The Nature of the Research Enterprise
When practitioners from two fields collaborate, each brings to the table the values that characterize
each field. Given the importance that biologists place on the understanding of specific biological phe-
nomena of interest, they place the highest value on answers that are specific to those phenomena.
Biologists want “the answer,” and they are interested in details of a computational model only insofar
as they have an effect on the answer; for the most part, they care far less about a hypothetical biological
phenomenon than about explaining the data obtained from experiment. Computer scientists and math-
ematicians, in contrast, are interested in the parameters of a model or a solution and in ways to improve