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Complex systems and systems biology
The field of complex systems is interested in the complicated systems consisting of many interacting components that occur in many different fields. Economic markets, ant colonies, the Internet and metabolic networks are all examples of complex systems. A fundamental characteristic shared by all these systems is that they can be described as a network in which nodes are components and edges between nodes are interactions between components. Each individual compononent in the system may be relatively system, however complex behaviour frequently emerges as a result of the interactions between large numbers of such simple components.
Within a context of a genetic regulatory network, the system parts are genes and proteins while the emergent properties of interest include oscillatory behaviour, pattern formation, robustness and a number of other complex control phenomena. The field of complex systems is highly interdisciplinary and much of the literature is focussed on systems in a particular domain, such as biology, ecology or economics, and the extrapolation of insights between domains. There is also a growing emphasis on general techniques, theories and insights that may be applied across domains [108].
Recently, the cooperative efforts of theoreticians and experimentalists have been embodied in the new field of systems biology [74]. The tools of systems biology are the large quantities of data generated by high-throughput experimental techniques and the increasingly sophisticated range of mathematical modelling techniques. The aim of systems biology is to integrate models at multiple biological scales and investigate systems-level properties of biological organisms. This aim includes understanding at four levels: (a) the structure of biological interaction networks; (b) their dynamics, how states change over time in different conditions; (c) the methods biological systems use to control the state of a cell; and (d) the design of systems, including both how they have evolved and how they may potentially be artificially constructed [73].
A key feature of systems biology is the integration of both theoretical modelling and empirical investigation, in which current biological knowledge informs the development of models and the analysis of these models produces a set of predictions that may then be tested in the laboratory (see Figure 4).
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Next: Key features of dynamic Up: A diversity of models Previous: Why build models? Nic Geard 2004-05-06