Modelling codependence in biological systems.
A central aim of systems biology is to elucidate the complex dynamic structure of biological systems within which functioning and control occur. The success of this endeavour requires a dialogue between the two quite distinct disciplines of life science and systems theory, and so drives the need for graphical notations which facilitate this dialogue. Several methods have been developed for modelling and simulating biochemical networks, some of which provide notations for graphicall4y constructing a model. Such notations must support the full panoply of mechanisms of systems biology, including metabolic, regulatory, signalling and transport processes. Notations in systems biology tend to fall into two groups. The first group derives its orientation from conventional biochemical pathway diagrams, and so tends to ignore the role of information processing. The second group focuses on the processing of information, incorporating information-processing ideas from other systems-oriented disciplines, such as engineering and business. This, however, can lead to the two crucial and related difficulties of impedance mismatch and conceptual baggage. Impedance mismatch concerns the rift between non-biological notations and biological reality, which forces the researcher to employ awkward workarounds when modelling uniquely biological mechanisms. Conceptual baggage can arise when, for instance, an engineering notation is adapted to cater for these distinctively biological needs, since these adaptations will, typically, never completely free the notation of the conceptual structure of its original engineering motivation. A novel formalism, codependence modelling, which seeks to combine the needs of the biologist with the mathematical rigour required to support computer simulation of dynamics is proposed here. The notion of codependence encompasses the transformation of both chemical substance and information, thus integrating both metabolic and gene regulatory processes within a single conceptual schema.
Mandel
J J
JJ
Department of Biotechnology & Bioinformatics, Weihenstephan University of Applied Sciences, Freising 85350, Germany. johannes.mandel@fh-weihenstephan.de
Palfreyman
N M
NM
Dubitzky
W
W
D003198:Computer Simulation; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology; D049490:Systems Biology / Q000379:methods*