Biology Reference
In-Depth Information
systems biology in addition to functional genomics should lead to a progression
of insight that is also outside the range covered by the primary dataset. The
developing insight is effectively a third dimension, which is one of the aspects
that systems biology may help add to functional genomics.
An example would be the observation in a large number of datasets that
mRNA for a protein A always goes up or down together with that of protein
B. This would lead to the empirical law that proteins A and B always behave
similarly. This empirical law would reside on the same conceptual plane as the
primary data set and would therefore fit into the cycle picture of Fig. 3. Here
the broad aim of functional genomics could be seen to have been satisfied, and
experimentation could stop. However, systems biology would search further for
the cellular control and regulation hierarchy to find that the two corresponding
genes are regulated by the same transcription factor; it would then search for
interactions responsible for the correlation. Not only would this explain the
observed correlation of mRNA-A and mRNA-B, it would also predict exceptions
to these correlations, e.g. when a second transcription-factor footprint would
map to gene A but not to gene B. In this way understanding will slowly but
steadily grow outside the primary data set and elucidate more and more of cell
biology, hence add a dimension of understanding.
We therefore recognize that systems biology may be among the sciences that is
better described by a spiral of knowledge rather than a cycle (cf. Fig. 4). A further
addition to the traditional vision is that of a box with overlying and underlying
theories, with a deductive arrow stemming from that (cf. Figs. 3 and 4). Indeed,
any law or hypothesis of systems biology should be consistent with underlying
physical-chemical principles and in good systems biology any such hypothesis
should therewith also be deduced in part from those underlying principles (this
may seem a superfluous remark but we have seen systems biology-type theories
that were inconsistent with the second law of thermodynamics and principles of
electric fields).
4.3.1. Systems biology: The inductive versus the deductive mode
The recent developments in postgenomics have caused the empirical branch of
systems biology, which is closest to functional genomics and stems from the
developments in molecular biology (Westerhoff & Palsson, 2004), to develop
most strongly. This branch emphasizes the observation component, i.e. the mea-
surement of the dynamic variables. It then establishes patterns in the observed
dynamic responses of the system to perturbations, whereby it uses mathematics
for the analysis of multidimensional systems. This functional genomics activity
tends towards systems biology because it accommodates the feature that the var-
ious molecules in the living cell vary coordinately in concentration. Often it is
not yet the science of systems biology because it sticks to the observation of the
correlations, without necessarily understanding their basis or whether they are
