title: Modelling cellular signalling systems.
abstract: Cell signalling pathways and networks are complex and often non-linear. Signalling pathways can be represented as systems of biochemical reactions that can be modelled using differential equations. Computational modelling of cell signalling pathways is emerging as a tool that facilitates mechanistic understanding of complex biological systems. Mathematical models are also used to generate predictions that may be tested experimentally. In the present chapter, the various steps involved in building models of cell signalling pathways are discussed. Depending on the nature of the process being modelled and the scale of the model, different mathematical formulations, ranging from stochastic representations to ordinary and partial differential equations are discussed. This is followed by a brief summary of some recent modelling successes and the state of future models.
authors.affiliation: Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, New York, NY 10029, U.S.A. padmini.rangamani@mssm.edu
authors.forename: Padmini
authors.initials: P
authors.lastname: Rangamani
authors.forename: Ravi
authors.initials: R
authors.lastname: Iyengar
mesh_terms: D000818:Animals; D002477:Cells / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological; D015203:Reproducibility of Results; D015398:Signal Transduction
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