Stochastic modelling for quantitative description of heterogeneous system. Nat Rev Genet

School of Mathematics & Statistics and the Centre for Integrated Systems Biology of Ageing and Nutrition, Newcastle University, Newcastle upon Tyne, Tyne and Wear NE1 7RU, UK.
Nature Reviews Genetics (Impact Factor: 36.98). 02/2009; 10(2):122-33. DOI: 10.1038/nrg2509
Source: PubMed


Two related developments are currently changing traditional approaches to computational systems biology modelling. First, stochastic models are being used increasingly in preference to deterministic models to describe biochemical network dynamics at the single-cell level. Second, sophisticated statistical methods and algorithms are being used to fit both deterministic and stochastic models to time course and other experimental data. Both frameworks are needed to adequately describe observed noise, variability and heterogeneity of biological systems over a range of scales of biological organization.

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    • "According to this fundamental memory-free hypothesis of Markov model and the Equation (1) and (2), at time t, the cell might eventually fall into slots as displayed in Figure 2a. The mathematical equations have been solved according to methods displayed in (Wilkinson, 2009). "
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