System Biology of Cell Signaling - Systems Biology Concepts and Insights - page 310

power of correlating genomic status with the dynamics of
physiological response [109] . As the systems we study
become progressively larger, the tight, rapid and iterative
coupling between experiments and modeling will become
necessary. Such iterative approaches hold the promise of
providing deep understanding of the mechanisms by which
molecular interactions control organ, multiorgan and
organismal level functions.

predicted from initial conditions. Typically such
systems involve interactions between cellular compo-
nents that exist in very low copy numbers.
Microdomains are compartmentalized regions within
a cell, often located in close proximity to the plasma
membrane, that transiently contain high concentrations
of activated signaling components. Microdomains may
consist of anything from a short-lived cluster of several
protein and lipid molecules to large organized domains
tens or hundreds of nanometres in diameter.

GLOSSARY
Bistability is an emergent property of a biological system
that allows the system to exist stably in two states, such
as active and inactive. The switch can by triggered by an
incoming stimulus. Usually positive feedback is
necessary for bistability, although it is not sufficient if
the levels of the components of the system or reaction
rates are not in the appropriate range.
Positive feedback occurs when a downstream protein
within a pathway is able to activate its upstream regu-
lator, resulting in the output signal being amplified with
respect to the input. It is observed both at a cellular level
and at tissue organ physiology level.
Negative feedback occurs when a downstream component
inhibits the activity of an upstream regulator. Func-
tionally a negative feedback loop will reduce output
signal and can linearize the input/output relationship. A
classic example is feedback inhibition of biosynthetic
enzymes by metabolites such that metabolites control
their levels within cells.
Coherent and incoherent feedforward motifs are orga-
nizational units (motifs) within networks. In a feedfor-
ward motif an upstream component has at least two
paths to a downstream component. Often one path is
longer than the other. A feedforward motif is called
coherent if both paths result in activation of the down-
stream component. If one of the paths is inhibitory the
feedforward loop is called incoherent.
Ordinary differential equations (ODEs) are used to
represent systems where the rate of change in the
variable of interest is determined with respect to one
other variable, most often time.
Partial differential equations (PDEs) are used to repre-
sent systems in which the variable of interest changes
with respect to two or more variables, most commonly
time and space.
Deterministic models are computational models repre-
senting systems whose time evolution is entirely
determined by the initial conditions. ODE and PDE
based models are deterministic models.
Stochastic models are used to represent systems where the
time evolution of the system has a probabilistic
component. The trajectory of such systems cannot be

ACKNOWLEDGMENTS
Research in our laboratory is supported by NIH grants GM54508 DK-
087650 and System Biology Center Grant GM-071558.

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