title: Models at the single cell level.
abstract: Many cellular behaviors cannot be completely captured or appropriately described at the cell population level. Noise induced by stochastic chemical reactions, spatially polarized signaling networks, and heterogeneous cell-cell communication are among the many phenomena that require fine-grained analysis. Accordingly, the mathematical models used to describe such systems must be capable of single cell or subcellular resolution. Here, we review techniques for modeling single cells, including models of stochastic chemical kinetics, spatially heterogeneous intracellular signaling, and spatial stochastic systems. We also briefly discuss applications of each type of model.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Raymond
authors.initials: R
authors.lastname: Cheong
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Saurabh
authors.initials: S
authors.lastname: Paliwal
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.|Whitaker Institute of Biomedical Engineering and Institute for Cell Engineering, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Andre
authors.initials: A
authors.lastname: Levchenko
mesh_terms: D000818:Animals; D002450:Cell Communication / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D011153:Population; D015398:Signal Transduction / Q000502:physiology; D059010:Single-Cell Analysis / Q000379:methods*; D013269:Stochastic Processes