title: Quantitative modeling in cell biology: what is it good for?
abstract: Recently, there has been a surge in the number of pioneering studies combining experiments with quantitative modeling to explain both relatively simple modules of molecular machinery of the cell and to achieve system-level understanding of cellular networks. Here we discuss the utility and methods of modeling and review several current models of cell signaling, cytoskeletal self-organization, nuclear transport, and the cell cycle. We discuss successes of and barriers to modeling in cell biology and its future directions, and we argue, using the field of bacterial chemotaxis as an example, that the closer the complete systematic understanding of cell behavior is, the more important modeling becomes and the more experiment and theory merge.
authors.affiliation: Department of Neurobiology, Physiology and Behavior, University of California, Davis, 95616, USA. mogilner@math.ucdavis.edu
authors.forename: Alex
authors.initials: A
authors.lastname: Mogilner
authors.forename: Roy
authors.initials: R
authors.lastname: Wollman
authors.forename: Wallace F
authors.initials: WF
authors.lastname: Marshall
mesh_terms: D021581:Active Transport, Cell Nucleus; D000818:Animals; D001419:Bacteria; D002453:Cell Cycle; D002633:Chemotaxis; D019295:Computational Biology / Q000379:methods*; D003599:Cytoskeleton / Q000502:physiology*; D005658:Fungi; D008954:Models, Biological; D008962:Models, Theoretical; D009010:Monte Carlo Method; D015398:Signal Transduction; D013269:Stochastic Processes