Biology Reference
In-Depth Information
of a new science should be welcome for a number of reasons. At present many
systems biologists are confronted in response to their papers or grant applications
that the science they are doing or proposing is not quite proper, being insuffi-
ciently driven by minimal hypotheses or being too mathematical for molecular
cell biology. Such responses may well derive from a lack of appreciation that
there is a paradigm shift to a new science which combines many of the earlier
scientific disciplines in a nonlinear way: some but not all the norms and values
of the earlier disciplines persist and new standards of how to do science emerge.
Establishment of those norms and values for the new science, or at least recogni-
tion that the new science will develop new standards on how to do science, may
accelerate the development of the new science by removing obstructions deriving
from misunderstanding or conservatism. By being relatively early, this topic may
play a unique role as compared to earlier topics on the philosophy of science.
When a new science paradigm comes into existence, response tends to evolve
according to the dictum: 'it is nothing new', through 'it is wrong' to 'I knew it
all along', where indeed there is an element of truth in all of these, but also an
element of conservatism and forgetfulness about the history of science. The same
words would apply to statistical thermodynamics or molecular biology. What is
clear from the above chapters is that the nature of systems biology is well defined
by now and that is does differ from pre-existing disciplines. By synergistically
combining theory, modeling and experiment, this discipline aims to obtain a
molecular mechanistic picture of cells to the extent that cellular behavior can be
understood in terms of the behavior of its constituent molecules and higher order
consortia thereof. This is possible only now and not, say, 15 years ago because
of the recent development of technologies critical to obtaining the required high-
quality and experimental data concerning virtually all components of the living
cell. Not all of these technologies are perfect yet, but it is anticipated that they
reach the required accuracy in not too long a time. These technologies offer
two complementary approaches to systems biology: top-down and bottom-up
systems biology. Top-down approaches start with experimental data concerning
the changes in abundancies of the molecules in the entire system to extract
knowledge about the molecular mechanisms that generated the data. Nowadays,
this can be done on an organism-wide scale using high-throughput measurements
of organisms perturbed by various means, such as changes in nutrient levels or
physicochemical environment. Bottom-up approaches start from the knowledge
about molecular mechanisms and determine whether our knowledge suffices by
comparing the behavior of molecular mechanisms in detailed computer models
to their
in vivo
behavior. Discrepancies then pinpoint gaps in our knowledge
and offer opportunities for new findings. Such an approach may also lead to the
discovery of new regulatory mechanisms.
This topic may help clarify many issues concerning the status of systems
biology and its methodology. Chapters of this topic have described research
