Physicochemical modelling of cell signalling pathways

By B. Aldridge, J. Burke, Douglas A. Lauffenburger, Peter K. Sorger. Nature Cell Biology, 2006

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Logic-Based Models for the Analysis of Cell Signaling Networks (2010, background): “Partial differential equations (PDEs) add the ability to represent spatial gradients (5), and stochastic methods make it possible to analyze systems in which the number of molecules is”
Rule-based modeling of biochemical systems with BioNetGen. (2009, background): “These transformations are (1) add a bond, (2) delete a bond, ( 3 ) change a component state label, (4) delete a molecule, or (5) add a molecule.”
Input–output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data (2009, background): “A second point of view holds that models should be as simple as possible as long as they reproduce empirical ﬁndings; ideally, models should have fewer degrees of freedom than training data (Aldridge et al , 2006).”