Cell
8
cesses (appropriately and importantly including both tational approaches, and address a greater scope of
biochemistry and biophysics/biomechanics facets of cell biologyproblems across hypothesis generation, hy-
dynamics). Some other areas at the forefront of cell pothesis testing,and intuition development. But achiev-
biology that could fall into this combination of categories ing that comfortable marriage will likely require a decade
are neglected; among these I might suggest protein and of continuing work by many researchers tackling a vari-
nucleic-acid regulatory processes underlying gene ex- ety of particular problems. In the meantime, this current
pression, ligand/receptor binding and trafficking pro- book is certainly the best available for the present early
cesses, and protein signal transduction networks. These courtship stage, and I will recommend it enthusiastically
are all exciting areas that should benefit tremendously to all my own students and colleagues.
from increased devotion of computational modeling ef-
forts. From a wider perspective, many dynamic molecu-
Douglas A. Lauffenburger
lar-level cell processes can be analyzed productively Biological Engineering Division and Bio logy Department
via computational techniques other than differential Massachusetts Institute of Technology
equations characterizing physico-chemical mecha- Cambridge, Massachusetts 02139
nisms. That is, while differential equations derived from
underlying mechanistic hypotheses are wonderfully ca-
pable of simulating dynamic processes to generate pre-
Another View of Developme ntal Biology?
dictions based on those hypotheses, at least two other
outstanding challenges in cell biology that could benefit
from computational analysis methods can be posed. Molecular Principles of Animal Development
One challenge is the elucidation of hypotheses, in By Alfonso Martinez Arias and Alison Stewart
the first place, for operation of a cellular process for Oxford: Oxford University Press (2002).
experimental systems in which the key molecular com- 350 pp. $42.95
ponents and the topology of their interactions are not
well established. An enticing promise of systems biol- Developmental biology sets out to explain how plants
ogy, in its genomics and proteomics and metabolomics and animals develop. This is a very complex problem
(etc.) mode, is efficient production of experimental data and, as such, its solution demands the use of techniques
that can be “mined” in an unbiased, “data-driven” man- from a variety of disciplines. Hence, developmental biol-
ner to glean potential relationships among variables of ogy today is a multidisciplinary endeavor that rests
interest. The types of computational techniques em- chiefly on four pillars: morphology (embryology), genet-
ployed for data-mining tasks are typically based on sta- ics, molecular biology, and cell biology. Its goal is to
tistical or vector space methods rather than on differen- provide as complete a description of ontogenesis as
tial equations, and are not treated in this particular text. possible, together with a causal explanation of the
The resulting potential relationships, of course, suggest mechanisms involved. By applying the techniques and
physico-chemical hypotheses for operation of the mo- way of thinking of four of the major parcels of biology
lecular components represented by the “omics” vari- to the search for a solution of the problem of “develop-
ables, which can then be transformed into differential ment,” researchers have achieved what might be con-
equation-based computational models for testing pre- sidered a synthesis of biological disciplines.
dictions thereof. This hypothesis-formation step is by The problem of “development”—where do we come
now the “traditional” domain of bioinformatics, but it is from and how do we come to be—has occupied the
nonetheless a significant area for computational cell human mind certainly since long before the Classical
biology in facilitating a swift growth in the number of period (see, for example, the discussion on Egyptian
experimental problems that can be addressed by the and Indian antiquity in Joseph Needham’s A History of
kind of physico-chemical models articulated in this text Embryology, Second Edition [New York: Abelard Schu-
at hand. man], 1959); embryological work goes back to the Pre-
An additional challenge is how to recover intuitive socratic period, at least. However, developmental biol-
insights about operation of a cell process of interest, ogy as the application of a combination of biological
even when successful simulation of the process by a disciplines to the solution of the problem of “develop-
physico-chemical differential equation model has been ment” is a very young science. In the late 1930s, Donald
achieved. Computational prediction of the outcome of Poulson started investigating embryonic Drosophila
the next experiment is essential for building confidence mutants to show that genes play a role in development
in the validity of the model hypotheses, but does not (Erwin Baur had collected and analyzed mutants affect-
necessarily simultaneously bring intuitive understanding ing flowering in snapdragons even earlier); and Joseph
about why that outcome was obtained. Here again the Needham, Conrad Waddington, Johannes Holtfreter,
type of mathematics that can be brought to bear on this
and others became interested in the chemical nature of
question may go beyond what is presented in this text.
Spemann’s “Organisator” around the same time. But 30
For instance, Boolean logic, Bayesian network, or Mar-
to 40 more years were to pass before, in the 1970s and
kov chain methods may be gainfully employed to discern
1980s, genetics and molecular biology, followed a little
how certain variables influence others or how multiple
later by cell biology, formed a partnership with embryol-
variables combine to influence an outcome.
ogy in a concerted and systematic attempt to analyze
Thus, as the field of computational cell biology contin-
how animals develop. A similar approach was soon
ues to grow, I anticipate further benefit will arise from
adopted to understand plant development. Since the
additional texts that comprise a broader set of cell biol-
ogy topics anda morecomprehensive batteryof compu- early 1980s, the scientific strategy of dissecting devel-
