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Quantitative kinetic modeling software tools | Mathematical modeling

Kinetic modeling of complex biochemical systems is central to the emerging field of systems biology (Kitano, 2002; Le Novère, 2015). Kinetic models require definition of numerous free parameters, usually obtained by calibration to experimental data, that specify initial species concentrations and kinetic rate constants. Once calibrated, a model should be analyzed for its sensitivity and predictive power over ranges of parameter values (Fisher and Henzinger, 2007). Both model calibration and analysis can require thousands to millions of model simulations for statistical convergence and significance (Eydgahi et al., 2013; Gutenkunst et al., 2007). In many cases, the computational expense of simulation at this scale makes detailed model analysis infeasible.

References:
(Kitano, 2002) Computational systems biology. Nature.
(Le Novere, (2015) Quantitative and logic modelling of molecular and gene networks. Nat Rev Genet.
(Fisher and Henzinger, 2007) Executable cell biology. Nat Biotechnol.
(Eydgahi et al., 2013) Properties of cell death models calibrated and compared using Bayesian approaches. Mol Syst Biol.
(Gutenkunst et al., 2007) Universally sloppy parameter sensitivities in systems biology models. PLoS Comput Biol.

Source text:
(Harris et al., 2017) GPU-powered model analysis with PySB/cupSODA. Bioinformatics.

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