%0 Journal Article %1 Cheong2010Models %A Cheong, Raymond %A Paliwal, Saurabh %A Levchenko, Andre %C 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 %D 2010 %I John Wiley & Sons, Inc. %J Wiley Interdisciplinary Reviews: Systems Biology and Medicine %K modelling multi-scale-modelling systems-biology %N 1 %P 34--48 %R 10.1002/wsbm.49 %T Models at the single cell level %U http://dx.doi.org/10.1002/wsbm.49 %V 2 %X Abstract 10.1002/wsbm.49.abs 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 \copyright 2009 John Wiley & Sons, Inc. For further resources related to this article, please visit the WIREs website.

@article{Cheong2010Models, abstract = {Abstract 10.1002/wsbm.49.abs 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 {\copyright} 2009 John Wiley \& Sons, Inc. For further resources related to this article, please visit the {WIREs} website.}, added-at = {2018-12-02T16:09:07.000+0100}, address = {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}, author = {Cheong, Raymond and Paliwal, Saurabh and Levchenko, Andre}, biburl = {https://www.bibsonomy.org/bibtex/2831e7797802c9a30a53e750edb0e43fc/karthikraman}, citeulike-article-id = {5779129}, citeulike-linkout-0 = {http://dx.doi.org/10.1002/wsbm.49}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/122513751/ABSTRACT}, doi = {10.1002/wsbm.49}, interhash = {cc30866e7f591652256cc1208e1c7e8c}, intrahash = {831e7797802c9a30a53e750edb0e43fc}, issn = {19395094}, journal = {Wiley Interdisciplinary Reviews: Systems Biology and Medicine}, keywords = {modelling multi-scale-modelling systems-biology}, month = jan, number = 1, pages = {34--48}, posted-at = {2010-04-19 09:01:09}, priority = {2}, publisher = {John Wiley \& Sons, Inc.}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Models at the single cell level}, url = {http://dx.doi.org/10.1002/wsbm.49}, volume = 2, year = 2010 }