4.3 Behavioral Complexity of Biomolecular Systems


4.3 Behavioral Complexity of Biomolecular Systems

Diverse and important examples of high behavioral complexity are shown by biomolecular and biological systems at different levels of their organization and structure.

Complex oscillatory processes in a human brain are known to occur at the tissue level. Heart rhythm disturbances and sudden-death phenomenon can be determined by pathological modes of myocardium excitation (Winfree 1994). Complex dynamic regimes lead to a ordered spatial evolution at the level of cell assembly—for instance, in the formation of nonuniform circular cell distributions in thin layers of dictyostellum discoideum media (Prigogine 1980). Oscillating modes in concentration levels were found for diverse chemical and biochemical reactions in biological membranes and cells (i.e., at the supramolecular level; Goldbetter 1997). Finally, complex dynamics can be considered as the origin of collective excitations in biomacromolecules at the molecular level (Davydov 1984).

One of the basic points in understanding an information processing system is the correlation between its structural and behavioral complexity (Nicolis 1986). It is quite often assumed (e.g., in the case of electronic technical systems) that behavioral complexity should increase proportionally to increasing structural complexity. Nevertheless, the correlation between structural and behavioral complexity is not straightforward. Increased complexity of the system structure does lead in many cases to more complicated behavior, but at the same time, some very simple systems (for instance, two oscillators with nonlinear coupling) are known that demonstrate complex behavior in spite of the simplicity of their structure.

Regrettably, there are no general theoretical approaches to explain what the structure (and other characteristics) of a system should be to provide predetermined complexity of the behavior. Based on experimental experience and theoretical considerations, two basic principles could be stated that determine high behavioral complexity of the system:

  • Nonlinear mechanisms in the system dynamics

  • A multilevel structural organization with interaction between different levels

Nonlinear biochemical enzymatic systems and chemical oscillators represent striking examples of very complex behavior based on primitive structures. Thin layers of these reagents demonstrate different complex modes of behavior, such as concentration oscillations, waves of switching between different states, traveling concentration pulses, stable dissipate structures, and so on (Field and Burger 1985).

Two examples of temporal evolution of a Belousov-Zhabotinsky system are shown in figure 4.1.

click to expand
Figure 4.1: Two modes of a Belousov-Zhabotinsky reaction in thin (pseudo two dimensional layers of the reagent. (A) A process of trigger wave spreading corresponding to the switching of the medium from one stable state to another; (B) an emission of circular waves from point-wise sources and their further evolution. Here and in the following figures gray arrows show steps of the image transformation by the reaction-diffusion medium, black arrows correspond to input of an initial image into medium.

The remarkable feature of such biomolecular systems is that they are capable of fulfilling functions adequate for information processing operations of high computational complexity. Aside from the fantastic intellectual capabilities of a neural system, let us mention the processes of information replication performed by RNA molecules, the recognition at the molecular level inherent in enzyme molecules, and so on.

This feature of biomolecular systems lies behind the basis of the pseudobiological information processing paradigm that is an important alternative to the presently unique von Neumann approach in contemporary digital computing.




Molecular Computing
Molecular Computing
ISBN: 0262693313
EAN: 2147483647
Year: 2003
Pages: 94

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