Predicting rates of cell state change caused by stochastic fluctuations using a data-driven landscape model

We develop a potential landscape approach to quantitatively describe experimental data from a fibroblast cell line that exhibits a wide range of GFP expression levels under the control of the promoter for tenascin-C. Time-lapse live-cell microscopy provides data about short-term fluctuations in prom...

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Veröffentlicht in:	Proceedings of the National Academy of Sciences - PNAS 2012-11, Vol.109 (47), p.19262-19267
Hauptverfasser:	Sisan, Daniel R, Halter, Michael, Hubbard, Joseph B, Plant, Anne L
Format:	Artikel
Sprache:	eng
Schlagworte:	Animals Biological Sciences Cell lines Cell Proliferation Cells Computer Simulation Coordinate systems Cytometry Diffusion Diffusion coefficient diffusivity Epigenesis, Genetic Epigenetics equations fibroblasts Fibroblasts - cytology Fibroblasts - metabolism Flow Cytometry Gene expression Genotype & phenotype Green Fluorescent Proteins - metabolism Kinetics Measurement Mice microscopy Models, Biological NIH 3T3 Cells phenotype Phenotypes Pluripotent stem cells Population distributions prediction Simulation Stem cells Stochastic Processes
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