%0 Journal Article
%T A general framework for modeling growth and division of mammalian cells
%A John H Gauthier
%A Phillip I Pohl
%J BMC Systems Biology
%D 2011
%I BioMed Central
%R 10.1186/1752-0509-5-3
%X A framework for modeling complex cell-biologic processes is proposed here. The framework is based on two constructs: one describing the entire lifecycle of a molecule and the second describing the basic cellular machinery. Use of these constructs allows complex models to be built in a straightforward manner that fosters rigor and completeness. To demonstrate the framework, an example model of the mammalian cell cycle is presented that consists of several hundred differential equations of simple mass action kinetics. The model calculates energy usage, amino acid and nucleotide usage, membrane transport, RNA synthesis and destruction, and protein synthesis and destruction for 33 proteins to give an in-depth look at the cell cycle.The framework presented here addresses how to develop increasingly descriptive models of complex cell-biologic processes. The example model of cellular growth and division constructed with the framework demonstrates that large structured models can be created with the framework, and these models can generate non-trivial descriptions of cellular processes. Predictions from the example model include those at both the molecular level--e.g., Wee1 spontaneously reactivates--and at the system level--e.g., pathways for timing-critical processes must shut down redundant pathways. A future effort is to automatically estimate parameter values that are insensitive to changes.Most researchers keep a serviceable mental model of how molecules of interest react with each other in various cellular pathways. Such qualitative models suffice for many purposes. They can, however, break down when trying to explain more complex interactions between molecules, e.g., when a molecule participates in multiple pathways; when the activity or the appearance of the molecule is dependent on multiple reactions; when the timing of reactions is important; when multiple processes interact, etc. For such reasons, quantitative modeling of complex biologic processes, such as the
%U http://www.biomedcentral.com/1752-0509/5/3