Biomedical Engineering Reference
In-Depth Information
from investigation of the modular description of components. "Rules" emerged
from intra-modular knowledge and "exceptions" from unidentified inter-modular
interactions, an unchartered biological territory—until recently. Biology has
undergone a remarkable transition: from single investigator-driven to multi-
investigator-driven research. Nowadays it is fashionable to talk of a special bio-
logical metamorphosis called "Systems Biology." Systems biology is an
emer-
gent
phenomenon that arose from a need to combine biology with mathematics,
physics, chemistry, and computer science.
Analysis of the cell in its entirety assumes importance in view of the fuzzy
boundaries that exist among pathways. Crosstalk among cellular pathways exists
among functionally specialized components, e.g., DNA polymerase, which both
acts as a catalyst for synthesizing new strands and communicates with the cell
repair machinery. The DNA polymerase "interface" is indicative of the fact that
a given cellular component may be connected both upstream and downstream
into a mesh of transactions. These transactions bring about dynamic interaction
among otherwise "static" genes and proteins. The whole cell network is exten-
sive, demonstrates nonlinearity, and is difficult to describe in terms of concen-
trations alone. The origin of nonlinearity lies in the feedback loops, rate
constants, and the inherent randomness and noise in gene expression, in addition
to coupled vector and scalar processes. Considering cellular events as entirely
modular processes is therefore an intrinsically error-prone assumption. Systems
biology deals with these issues and offers an in-silico view of the genetic and
metabolic pathways, thus providing a clear mechanistic basis as well as a practi-
cal view of a biological process, especially the emergent phenomena.
Ever since in-silico modeling paved the way for creation of the first hypo-
thetical virtual cell (34), researchers have been aggressively pushing the case for
creating more complicated virtual systems. The challenge is not only to simulate
a reaction, but to simulate it
accurately
in the presence of diverse physiological
conditions and feedback loops. Figure 1 shows a schematic representation of
quantitative modeling of cellular processes. In the following sections we review
some of the background work, modeling, and simulation tools—especially E-
Cell—and the progress we expect to see in this field.
2.
BIOMEDICAL BACKGROUND
The idea of systems biology is not new. In 1948 Norbert Wiener took a sys-
tems approach in search of general biological laws and posited the principles of
cybernetics (38). Though his attempt was new and farsighted, his timing was not
right due to the nonavailability of biological data. Throughout the 1960s and
1970s researchers from the fields of mathematics and engineering
enthusiastically pursued the idea of transferring knowledge from physics to
