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

Proceedings of the National Academy of Sciences of the United States of America

Volumn 109, Issue 47, 2012, Pages 19262-19267

  Sisan, Daniel R ^a   Halter, Michael ^a   Hubbard, Joseph B ^a   Plant, Anne L ^a  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

Author keywords

Biological noise; Dynamical systems; Population distribution; Stochastic protein expression

Indexed keywords

GREEN FLUORESCENT PROTEIN; TENASCIN;

ACCURACY; ANIMAL CELL; ANIMAL TISSUE; ARTICLE; CELL ISOLATION; CELL KINETICS; CELL MEMBRANE POTENTIAL; CELL SUBPOPULATION; DIFFUSION COEFFICIENT; FIBROBLAST; FLOW CYTOMETRY; MATHEMATICAL MODEL; MICROSCOPY; MOLECULAR DYNAMICS; MOUSE; NOISE; NONHUMAN; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; PROTEIN EXPRESSION; QUANTITATIVE ANALYSIS; STEADY STATE; STOCHASTIC MODEL; TIME LAPSE IMAGING;

ANIMALS; CELL PROLIFERATION; COMPUTER SIMULATION; DIFFUSION; EPIGENESIS, GENETIC; FIBROBLASTS; FLOW CYTOMETRY; GREEN FLUORESCENT PROTEINS; MICE; MODELS, BIOLOGICAL; NIH 3T3 CELLS; STOCHASTIC PROCESSES;

EID: 84869755989     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1207544109     Document Type: Article

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