Mathematical modeling of complex regulatory networks.
Cellular regulation comprises overwhelmingly complex interactions between genes and proteins that ultimately will only be rendered understandable by employing formal approaches. Developing large-scale mathematical models of such systems in an efficient and reliable way, however, requires careful evaluation of structuring principles for the models, of the description of the system dynamics, and of the experimental data basis for adjusting the models to reality. We discuss these three aspects of model development using the example of cell cycle regulation in yeast and suggest that capturing complex dynamic networks is feasible despite incomplete (quantitative) biological knowledge.
Stelling
Jörg
J
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg 39106, Germany. stelling@mpi-magdeburg.mpg.de
Gilles
Ernst Dieter
ED
D002453:Cell Cycle / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D005786:Gene Expression Regulation / Q000502:physiology*; D006706:Homeostasis / Q000502:physiology; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000502:physiology*; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D014157:Transcription Factors / Q000378:metabolism
D029701:Saccharomyces cerevisiae Proteins; D014157:Transcription Factors