title: The dynamic systems approach to control and regulation of intracellular networks.
abstract: Systems theory and cell biology have enjoyed a long relationship that has received renewed interest in recent years in the context of systems biology. The term 'systems' in systems biology comes from systems theory or dynamic systems theory: systems biology is defined through the application of systems- and signal-oriented approaches for an understanding of inter- and intra-cellular dynamic processes. The aim of the present text is to review the systems and control perspective of dynamic systems. The biologist's conceptual framework for representing the variables of a biochemical reaction network, and for describing their relationships, are pathway maps. A principal goal of systems biology is to turn these static maps into dynamic models, which can provide insight into the temporal evolution of biochemical reaction networks. Towards this end, we review the case for differential equation models as a 'natural' representation of causal entailment in pathways. Block-diagrams, commonly used in the engineering sciences, are introduced and compared to pathway maps. The stimulus-response representation of a molecular system is a necessary condition for an understanding of dynamic interactions among the components that make up a pathway. Using simple examples, we show how biochemical reactions are modelled in the dynamic systems framework and visualized using block-diagrams.
authors.affiliation: Department of Computer Science, Systems Biology and Bioinformatics Group, University of Rostock, Albert Einstein Str. 21, 18059 Rostock, Germany. olaf.wolkenhauer@uni-rostock.de
authors.forename: Olaf
authors.initials: O
authors.lastname: Wolkenhauer
authors.forename: Mukhtar
authors.initials: M
authors.lastname: Ullah
authors.forename: Peter
authors.initials: P
authors.lastname: Wellstead
authors.forename: Kwang-Hyun
authors.initials: KH
authors.lastname: Cho
mesh_terms: D000818:Animals; D025461:Feedback, Physiological; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D015398:Signal Transduction