title: Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.
abstract: Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.
authors.affiliation: Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
authors.forename: Holger
authors.initials: H
authors.lastname: Conzelmann
authors.forename: Ernst-Dieter
authors.initials: ED
authors.lastname: Gilles
mesh_terms: D008433:Mathematics; D008954:Models, Biological; D046912:Multiprotein Complexes / Q000737:chemistry / Q000378:metabolism; D015398:Signal Transduction; D013816:Thermodynamics
chemical_list: D046912:Multiprotein Complexes