Joseph W. Lengeler
Metabolic Networks: a Signal-Oriented Approach to Cellular Models
Complete genomes, far advanced proteomes, and
even ‘metabolomes’ are available for at least a few organisms,
e. g., Escherichia coli. Systematic functional
analyses of such complete data sets will produce a
wealth of information and promise an understanding
of the dynamics of complex biological networks and
perhaps even of entire living organisms. Such complete
and holistic descriptions of biological systems,
however, will increasingly require a quantitative analysis
and the help of mathematical models for simulating
whole systems. In particular, new procedures are required
that allow a meaningful reduction of the information
derived from complex systems that will consequently
be used in the modeling process. In this review
the biological elements of such a modeling procedure
will be described. In a first step, complex living
systems must be structured into well-defined and
clearly delimited functional units, the elements of
which have a common physiological goal, belong to
a single genetic unit, and respond to the signals of a
signal transduction system that senses changes in
physiological states of the organism. These functional
units occur at each level of complexity and more complex
units originate by grouping several lower level
elements into a single, more complex unit. To each
complexity level corresponds a global regulator that is
epistatic over lower level regulators. After its structuring
into modules (functional units), a biological system
is converted in a second step into mathematical sub-models
that by progressive combination can also be
assembled into more aggregated model structures.
Such a simplification of a cell (an organism) reduces its
complexity to a level amenable to present modeling
capacities. The universal biochemistry, however, promises
a set of rules valid for modeling biological systems,
from unicellular microorganisms and cells, to
multicellular organisms and to populations.
Biological Chemistry, Walter de Gruyter
Print ISSN: 1431-6730
Volume: 381, 09/2000
Pages: 911 - 920
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