Open AccessModels at the single cell level
Author(s) -
Cheong Raymond,
Paliwal Saurabh,
Levchenko Andre
Publication year - 2010
Publication title -
wiley interdisciplinary reviews: systems biology and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.087
H-Index - 51
eISSN - 1939-005X
pISSN - 1939-5094
DOI - 10.1002/wsbm.49
Subject(s) - stochastic modelling , computer science , systems biology , population , single cell analysis , mathematical model , biological system , stochastic process , cell , computational biology , chemistry , biology , mathematics , statistics , demography , sociology , biochemistry
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. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Models of Systems Properties and Processes > Cellular Models