Modeling of cellular processes: methods, data, and requirements.
Systems biology is a comprehensive quantitative analysis how the components of a biological system interact over time which requires an interdisciplinary team of investigators. System-theoretic methods are applied to investigate the system's behavior. Using known information about the considered system, a conceptual model is defined. It is transferred in a mathematical model that can be simulated (analytically or numerically) and analyzed using system-theoretic tools. Finally, simulation results are compared with experimental data. However, assumptions, approximations, and requirements to available experimental data are crucial ingredients of this systems biology workflow. Consequently, the modeling of cellular processes creates special demands on the design of experiments: the quality, the amount, and the completeness of data. The relation between models and data is discussed in this chapter. Thereby, we focus on the requirements on experimental data from the perspective of systems biology projects.
Systems Biology & Bioinformatics, Institute of Computer Science, University of Rostock, Rostock, Germany. thomas.millat@uni-rostock.de
Thomas
T
Millat
Olaf
O
Wolkenhauer
Ralf-Jörg
RJ
Fischer
Hubert
H
Bahl
D002477:Cells / Q000378:metabolism*; D003198:Computer Simulation; D019992:Databases as Topic; D004798:Enzymes / Q000378:metabolism; D006863:Hydrogen-Ion Concentration; D007700:Kinetics; D008954:Models, Biological; D056004:Molecular Dynamics Simulation; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods*
D004798:Enzymes